Staff PRODUCT ENGINEER (Contract)

Build it. Ship it. Own it.

Location: Argentina, Brazil, Colombia, Chile, Mexico, Dominican Republic, Peru

About Counterpart

Counterpart is an insurtech platform reimagining management and professional liability for the modern workplace. We believe that when businesses lead with clarity and confidence, they become more resilient, more innovative, and better prepared for what's ahead. That's why we built the first Agentic Insurance™ system — where advanced AI and deep insurance expertise come together to proactively assess, mitigate, and manage risk. Backed by A-rated carriers and trusted by brokers nationwide, our platform helps small businesses grow with confidence. Join us in shaping a smarter future, helping businesses Do More With Less Risk®.

The Role

As a Product Engineer at Counterpart, you own problems and drive outcomes. You iron out requirements with stakeholders, partners, and customers. You leverage AI for implementation. You verify the end-to-end result. You iterate until you move the needle.

You run projects with other Product Engineers and AI agents. You know when to delegate to a human, when to delegate to an agent, and when to do it yourself. 

YOU WILL

Own the Problem

• Take accountability for the outcome. 
• Talk directly to your users, stakeholders, and peers to discover the problem. 
• Translate business intents into functional requirements that engineers and agents can build against. Determine where human judgment is non-negotiable and where AI can augment or act autonomously. 
• Own the non-functional technical requirements. Specify the quality bar: performance, scalability, reliability, security, maintainability.

Build with AI

• Write production-quality code across the stack: Python, Django, AWS, React, and PostgreSQL. You are not afraid of any layer.
• Direct agents and review their output with domain depth. Catch what they miss across the functional and non-functional bar: correctness, edge cases, performance, security, testability, readability.
• Evaluate and improve agent output regularly. Track failure modes. Refine the prompts and patterns that lift the quality ceiling over time.
• Run projects that span other Product Engineers and agents. Coordinate work, manage dependencies, and keep things moving without micromanaging.
• Contribute to architectural decisions. Bring options and alternatives, not objections. Know when the elegant solution is the wrong call for a startup moving fast.
• Contribute to and manage the context harness as you build and deliver.

Verify and Iterate

• Surface delivery risks early. Bring solutions, not just problems. Keep your stakeholders informed without turning every risk into a meeting.
• Verify the end-to-end result yourself. Confirm the system does what the requirements say, and that the requirements were right.
• Drive adoption of what you ship. Documentation, enablement, and usage monitoring are part of the job.
• Monitor your services in production. Own the signal. Debug and fix what breaks.
• Participate in support rotations. When users run into issues with what you shipped, you investigate and fix them.
• Iterate until you move the needle. Shipping is not the finish line. Outcome is.

Raise the Bar

• Mentor engineers around you. Give direct, useful feedback. Leave things better than you found them.
• Make deliberate calls on technical debt: when to accumulate it, when to pay it down, when to refactor. Translate trade-offs into language that business leaders can act on.
• Operate to the engineering standards for quality, reliability, and operational excellence.

YOU HAVE

• 10+ years building production web applications across the full stack. The years are the floor, not the bar. What matters is whether you have actually done this: owned a problem end-to-end, written the spec, built the thing, coordinated the work, and shipped it without someone else holding the thread.
• Demonstrated experience gathering requirements directly. You have interviewed users, customers, and partner teams, and turned ambiguous intent into specs that engineers and agents can build against.
• Demonstrated experience owning both functional and non-functional requirements. You have defined what a system must do and held the line on how well it must do it.
• A track record of owning a domain or initiative without close supervision. You have navigated ambiguity, made judgment calls, and been accountable for the outcome.
• Extreme ownership and a bias for action. You do not sit and wait. You chase stakeholders, customers, and answers when you need them.
• Experience coordinating across engineers and AI agents on a shared initiative. You have managed the work without holding a formal management title.
• Strong technical judgment and the depth to catch what AI-generated code gets wrong: not syntax, but correctness, architecture, intent.
• Proficiency with Python and Django. Working knowledge of TypeScript, React, and PostgreSQL.
• Proficiency in developing with AI tools (Claude Code, Cursor, OpenAI Codex, similar) and the drive to stay ahead of how AI development practices are evolving.
• Domain curiosity. You learn the business context your work supports, not just the systems. You understand why the problem matters, not just how to solve it.
• The ability to communicate clearly across engineering, product, and business, translating technical complexity without losing meaning.
• Low ego and high Emotional Quotient (EQ). You influence without authority, take feedback well, and leave your ego out of technical decisions.
• Experience working with distributed, remote teams.

HOW THIS ROLE WORKS

Product Engineering exists to collapse the distance between a problem and a working solution. You own a problem or part of a vision. You shape it with stakeholders. You build it with AI. You verify it end-to-end. You iterate until the metric moves.

You work within the Context Architecture, a shared system of documentation, design patterns, and domain knowledge that gives you the technical context to make autonomous decisions at every step.

This is not a role for engineers who need to be told how. It is a role for engineers who can take a problem, fill in the gaps with good judgment, and ship something that works.

WHO YOU WILL WORK WITH

• Derrick Franco, Principal Engineer: After teaching himself to code at 13, Derrick went on to co-found Jumpstart in addition to building out the technical divisions at InvestorsAlley and Phinaz Media Group. Nowadays Derrick spends his time reading, with his wife, and working on his podcast The Future of Work Project.
• Julian Prokay, Principal Engineer: A veteran of the SaaS space with experience working on both student systems and construction management software. In his free time, he enjoys history podcasts and fantasy literature.
• Tony Nguyen, Engineering Manager: Tony is an engineering and platform leader with 25+ years of leadership experience at companies like Sony PlayStation Network, Intuit TurboTax, and ServiceNow. He thrives at building products, scaling teams, and leading organizations, but more so building people. He believes the best leadership and engineering comes from bringing your full identity to work. For him that's faith, family, and sports! Outside of work, you can catch him on the couch with his 3 adult children watching anime, going to Disneyland, or having game nights.
• Ron Alexessen, Engineering Manager: With experience at Hewlett-Packard, New Relic, Rackspace, and consulting agencies, Ron has built teams and shaped technical culture across different environments. He's passionate about AI-enabled development as a force multiplier and building solutions that create real business impact. Outside work, he boulders, runs, rides gravel bikes, and co-parents active teenagers, embracing structured chaos in all of it.
• Newton Truong, Engineering Manager: Newton joins Counterpart with 7+ years of experience in platform and data engineering. In his last company Thrive Market, he had a hand in building out new microservices and architecting data pipelines with Airflow and Spark. He's vegetarian and loves trying new restaurants when traveling. Nowadays he's busy keeping up with his 2-year-old and doing outdoor activities with his family.
• John Mendez, Engineering Manager: John has experience working at companies of all sizes. He enjoys startups and small-to-medium businesses, where he can wear multiple hats and help deliver solutions. Outside of work, he stays busy with his four kids and their activities. He also makes time to stay active by working out at home and running or walking with his dog.

COUNTERPART'S VALUES

• Conjoin Expectations - it is the cornerstone of autonomy. Ensure you are aware of what is expected of you and clearly articulate what you expect of others.
• Speak Boldly & Honestly - the only failure is not learning from mistakes. Don't cheat yourself and your colleagues of the feedback needed when expectations aren't being met.
• Be Entrepreneurial - control your own destiny. Embrace action over perfection while navigating any obstacles that stand in the way of your ultimate goal. Leverage AI ruthlessly. We measure success by outcomes, not lines of code written. Use every available AI tool to ship faster and think more strategically.
• Practice Omotenashi ("selfless hospitality") - trust will follow. Consider every interaction with internal and external partners an opportunity to develop trust by going above and beyond what is expected.
• Hold Nothing As Sacred - create routines but modify them routinely. Take the time to reflect on where the business is today, where it needs to go, and what you have to change in order to get there.
• Prioritize Wellness - some things should never be sacrificed. We create an environment that stretches everyone to grow and improve, which is fulfilling, but is only one part of a meaningful life.

WE OFFER

1. Work from Anywhere - Counterpart is a fully distributed company, meaning there is no office. We allow employees to work from wherever they do their best work, of course prioritizing meetings that often happen in US time zones.
2. Language Classes - We sponsor up to $100 per calendar year to be used towards language classes to help support your English language skills.
3. Paid Vacation and Time Off
4. Parental Leave - Development Partners will be eligible for unpaid Parental Leave to bond with a newborn, newly-adopted, or newly placed child. Under this policy, development partners and independent contractors will be eligible for up to 8 weeks of unpaid parental leave. Any time off will be subject to approval and must be requested at least 45 days in advance.
5. Computer - We reimburse you for your locally procured MacBook Pro. If you are still with the company after one year, it is yours to keep!

Our estimated pay range for this role is USD $90,000 - $110,000 annually. Contractor compensation is determined by a variety of factors, including but not limited to, market data, location, internal equitability, and experience.

We are committed to being a welcoming and inclusive workplace for everyone, and we are intentional about making sure people feel respected, supported and connected at work, regardless of who you are or where you come from. We value and celebrate our differences and we believe being open about who we are allows us to do the best work of our lives.

We are an Equal Opportunity Employer. We do not discriminate against qualified applicants or employees on the basis of race, color, religion, gender identity, sex, sexual preference, sexual identity, pregnancy, national origin, ancestry, citizenship, age, marital status, physical disability, mental disability, medical condition, military status, or any other characteristic protected by federal, state, or local law, rule, or regulation.

We are looking for passionate technologists to join our Solution Consulting organization, to support our Customer Organization to ensure that our growth is grounded and guided by strong technical alignment with our platform and the needs of our customers. 

In this role, you are responsible for guiding our customers and users to design and build reliable, scalable systems using our data platform. Our team is made up of seasoned technical sales professionals, consultants, software architects, and developers who take direct responsibility for customer success, including the design of their software, deployment, and operations. 

You'll work closely with our Customer Success Managers and Relationship Account Managers to help customers solve business problems by leveraging our solutions. You'll become the trusted advisor to a wide range of customers from startups to the world's largest enterprise IT organizations.

This role will be based remotely in Mexico City or São Paulo. 

As an ideal candidate, you will have:

• 5+ years professional work experience within software development, consulting, Pre-Sales, or related fields.
• 2+ years of Pre-Sales experience with enterprise software 
• 2+ years of software development experience, with working knowledge and ability to code with one or more modern scripting languages (e.g. Python, Node.js, SQL) and/or popular programming languages (e.g. C/C++, Java, C#)
• A mind for technology - we’ll teach you all about MongoDB and databases, but our customers and products are inherently technical and you should have an aptitude and curiosity to learn about those concepts
• Experience with or knowledge of scalable and highly available distributed systems 
• Excellent presentation and communication skills 
• The ability to be adaptive to an ever-changing environment, where you are constantly improving yourself, your team and (y)our processes
• High levels of organization in your workflows - you understand what it means to work with lots of customers and to prioritize and manage your time efficiently
• The ability to travel up to 25%
• A Bachelor’s degree in Computer Science, MIS or similar degree or equivalent work experience
• Requires professional proficiency in both written and verbal English communication

As an ideal candidate, you may also have:

• Experience selling databases and/or deploying applications with any of the major cloud providers
• Experience with database programming and data models
• A MongoDB Certification

What you do at MongoDB

• You confidently articulate the business value of MongoDB solutions
• You partner with our Customer Organization to help ensure success in accounts ranging from small startups to large enterprises 
• You align to support remote/onsite sales with activities such as technical discovery, demos, presentation, sizing, and documentation of technical decision criteria; working across a number of opportunities in parallel
• You implement and maintain technology toolkits to drive compelling demonstrations and POCs
• You advise customers on architectures, patterns, and strategies for making the best use of MongoDB
• You assess and diagnose issue within a customer environment to provide recommendations about MongoDB best practices
• You translate technical concepts and patterns into business benefits
• You will have the opportunity to help drive demand through participation in both industry-known trade-shows as well as account-based marketing events
• You demonstrate resilience and sound judgment in dealing with business challenges
• You have an ability to drive customer demand within a sales territory, by being self-motivated, proactive and understanding the importance of a strong sense of urgency
• You have situational awareness and react appropriately in group settings

What you will learn

• The rapidly expanding MongoDB product suite, including:
• Core database server
• Atlas (fully managed cloud database service)
• Atlas Data Lake
• Atlas Full-Text Search
• Realm
• Charts
• Other Tools and connectors - Ops/Cloud Manager, Compass, Connector for BI, Connector for Spark
• Market-relevant, complementary technologies e.g. Apache Kafka, Kubernetes
• Modern and popular architecture design patterns, methodologies and concerns e.g. microservices, event-driven architectures, DevOps, cloud, security
• Sales techniques and related soft skills - presentations, demonstrations, whiteboarding, discovery, objection handling
• Exposure to a wide variety of market verticals and broad spectrum of interesting use cases

MongoDB is built for change, empowering our customers and our people to innovate at the speed of the market. We have redefined the database for the AI era, enabling innovators to create, transform, and disrupt industries with software. MongoDB’s unified database platform, the most widely available, globally distributed database on the market, helps organizations modernize legacy workloads, embrace innovation, and unleash AI. Our cloud-native platform, MongoDB Atlas, is the only globally distributed, multi-cloud database and is available across AWS, Google Cloud, and Microsoft Azure.

With offices worldwide and over 60,000 customers, including 75% of the Fortune 100 and AI-native startups, relying on MongoDB for their most important applications, we’re powering the next era of software.

Our compass at MongoDB is our Leadership Commitment, guiding how and why we make decisions, show up for each other, and win. It’s what makes us MongoDB. 

To drive the personal growth and business impact of our employees, we’re committed to developing a supportive and enriching culture for everyone. From employee affinity groups, to fertility assistance and a generous parental leave policy, we value our employees’ wellbeing and want to support them along every step of their professional and personal journeys. Learn more about what it’s like to work at MongoDB, and help us make an impact on the world!

MongoDB is committed to providing any necessary accommodations for individuals with disabilities within our application and interview process. To request an accommodation due to a disability, please inform your recruiter.

MongoDB is an equal opportunities employer.

Req ID: 1273424762

Company Background

Our client is a company that delivers integrated software and tools for the agricultural business. As part of a leading global software group, the company supports the diversified grain industry and agricultural co-ops with best-in-class solutions covering business management, commodity management, agronomy, trading, patronage, and analytics.

Project Description

Own the end‑to‑end data flow for Data Analytics Platform (DAP). You will ingest XML data from AGRIS Web Services into Azure Blob Storage, orchestrate event‑driven transformation pipelines via Azure Functions and Databricks Jobs, model data using dbt on Databricks (medallion architecture: bronze → silver → gold), and deliver analytics‑ready datasets to Azure SQL Database and Luzmo. You'll also maintain multi‑tenant data isolation, automate deployments, and keep the platform performant and cost‑efficient.

Technologies

• Microsoft Azure
• Azure Blob Storage / ADLS Gen2
• Databricks (Delta Lake, PySpark, SQL Warehouses)
• dbt (dbt-databricks + dbt-sqlserver)
• Azure Functions (Python)
• Azure Event Grid
• Azure SQL Database
• Azure Key Vault
• Luzmo

What You'll Do

• Maintain and support Azure Functions pipelines (Event Grid → Databricks Jobs);
• Build and optimize Databricks notebooks for XML parsing and Parquet landing in DBFS/ADLS;
• Manage Auto Loader and incremental data ingestion processes;
• Design and maintain dbt models across medallion layers (bronze COPY INTO, silver current‑changes, gold incremental merge, staging/CDC to Azure SQL);
• Write custom macros and ensure data quality with dbt tests;
• Optimize schemas, indexes, and CDC merge pipelines in Azure SQL Database;
• Manage analytical views, RBAC roles, and Luzmo integration for BI consumers;
• Maintain tenant‑scoped DBFS mounts and data isolation;
• Configure backup, storage tiering, and define RPO/RTO targets, monitor pipeline health;
• Automate deployments using CI/CD tools (e.g., GitHub Actions);
• Implement monitoring, alerting, and optimize infrastructure and compute costs in Azure and Databricks;

Job Requirements

• 5+ years designing and building data solutions on Microsoft Azure;
• 2+ years with Databricks (Delta Lake, PySpark, SQL Warehouses);
• Strong experience with dbt (data build tool): incremental models, custom macros, multi‑adapter setups (Databricks + SQL Server);
• Expert‑level SQL skills: Databricks SQL for Delta Lake transformations and T‑SQL for Azure SQL Database performance tuning;
• Hands‑on experience with Azure Functions (Python) and event‑driven architectures (Azure Event Grid, Blob Storage triggers);
• Familiarity with medallion architecture patterns (bronze/silver/gold) and CDC (Change Data Feed) pipelines;
• Working knowledge of XML data parsing/ingestion at scale (PySpark XML processing);
• Strong understanding of Azure security fundamentals (Key Vault, RBAC, managed identities);
• Experience with multi‑tenant data platform design and tenant‑scoped data isolation;
• English level: B1+ (Intermediate) or higher;

Nice to Have

• Microsoft Certified: Azure Data Engineer Associate (DP‑203) or Databricks Data Engineer Associate;
• Experience with IaC (Bicep or Terraform) and CI/CD (GitHub Actions);
• Familiarity with BI platforms, particularly Luzmo, for provisioning datasets and self‑service reporting;
• Knowledge of Python for Databricks notebooks, Azure Functions, and utility scripts;
• Experience with cost‑governance / FinOps in Azure and Databricks;
• Exposure to SQLFluff or similar SQL linting/quality tools;

What Do We Offer

The global benefits package includes:

• Technical and non-technical training for professional and personal growth;
• Internal conferences and meetups to learn from industry experts;
• Support and mentorship from an experienced employee to help you professional grow and development;
• Health insurance;
• English courses;
• Sports activities to promote a healthy lifestyle;
• Flexible work options, including remote and hybrid opportunities;
• Referral program for bringing in new talent;
• Work anniversary program and additional vacation days.

Project Description

We are looking for an experienced Data Engineer with deep expertise in Databricks to join our advanced analytics and data engineering team. The ideal candidate will play a key role in designing, building, and optimizing large-scale data solutions on the Databricks platform, supporting business intelligence, advanced analytics, and machine learning initiatives. You will collaborate with cross-functional teams to deliver robust, scalable, and high-performance data pipelines and architectures.

Technologies

• Databricks (including Spark, Delta Lake, MLflow)
• Python/Scala
• SQL
• ETL concepts
• Distributed data processing
• Data warehousing
• Cloud Platforms & Storage

What You'll Do

• Lead the design, development, and deployment of scalable data pipelines and ETL processes using Databricks (Spark, Delta Lake, MLflow);
• Architect and implement data lakehouse solutions, ensuring data quality, governance, and security;
• Optimize data workflows for performance and cost efficiency on Databricks and cloud platforms (Azure, AWS, or GCP);
• Collaborate with data scientists, analysts, and business stakeholders to understand data requirements and deliver actionable insights;
• Mentor and guide junior engineers, promoting best practices in data engineering and Databricks usage;
• Develop and maintain documentation, data models, and technical standards;
• Monitor, troubleshoot, and resolve issues in production data pipelines and environments;
• Stay current with emerging trends and technologies in data engineering and Databricks ecosystem;

Job Requirements

• Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, or a related field;
• 5+ years of experience in data engineering, with at least 2 years of hands-on experience with Databricks (including Spark, Delta Lake, and MLflow);
• Strong proficiency in Python and/or Scala for data processing;
• Deep understanding of distributed data processing, data warehousing, and ETL concepts;
• Experience with cloud data platforms (Azure Data Lake, AWS S3, or Google Cloud Storage);
• Solid knowledge of SQL and experience with large-scale relational and NoSQL databases;
• Familiarity with CI/CD, DevOps, and infrastructure-as-code practices for data engineering;
• Experience with data governance, security, and compliance in cloud environments;
• Excellent problem-solving, communication, and leadership skills;
• English: Upper Intermediate level or higher;

What Do We Offer

The global benefits package includes:

• Technical and non-technical training for professional and personal growth;
• Internal conferences and meetups to learn from industry experts;
• Support and mentorship from an experienced employee to help you professional grow and development;
• Health insurance;
• English courses;
• Sports activities to promote a healthy lifestyle;
• Flexible work options, including remote and hybrid opportunities;
• Referral program for bringing in new talent;
• Work anniversary program and additional vacation days.

Sep 25, 2025 12:50

About Orium

Orium builds smart, modern commerce solutions that help enterprise brands move faster and stay ahead.

By bringing together AI, data, and composable systems, we create experiences designed for collaboration between people and intelligent agents— helping our clients work more efficiently, adapt quickly, and gain a long-term competitive edge.

With more composable launches than any firm in the Americas and deep expertise across commerce architecture, we partner with leading technology providers to deliver scalable solutions that evolve with our clients and accelerate time to value.

We blend systems thinking, data-driven design, and intelligent delivery, embedding AI and agents into our own teams to move faster, reduce friction, and co-create with greater precision. The result: adaptive, cross-channel experiences that keep our clients ahead of what’s next.

About the Opportunity

Are you excited by solving meaningful technical problems and contributing to digital experiences used by thousands of people every day? As an Intermediate Software Developer at Orium, you’ll work closely with senior developers, designers, and product managers to help build modern ecommerce and composable commerce solutions for enterprise clients.

This role is ideal for someone with solid full-stack JavaScript experience, eager to grow, and seeking to deepen their expertise in modern frameworks, composable architecture, and AI-accelerated development practices. You’ll help build high-quality features, participate in code reviews, collaborate within an Agile team, and learn from seasoned technologists across Orium.

Responsibilities

• Collaborate with senior developers to design and implement features across front-end and back-end systems.
• Work with designers and Product Managers to estimate and plan work within an Agile framework.
• Communicate progress, risks, and technical considerations clearly with teammates.
• Create and maintain documentation that supports shared understanding across the team.
• Engage with clients alongside senior team members to support requirement gathering and demos.
• Write clean, maintainable, well-structured code following industry best practices.
• Participate in peer code reviews to help maintain high-quality, scalable codebases.
• Use modern AI-powered developer tools (e.g., GitHub Copilot, Claude Code, Devin, Codex) to improve development efficiency and spark new approaches to problem-solving.
• Apply responsible judgment in deciding when and how to use AI-assisted development tools.
• Explore opportunities to incorporate automation and AI into workflows (e.g., test scaffolding, documentation generation, debugging assistance).

Skills and Qualifications

• 3–5 years of industry experience as a full-stack JavaScript developer.
• Solid proficiency in modern web technologies: HTML, CSS, JavaScript, React.js, Next.js, Node.js, TypeScript, GraphQL, UI/Component libraries (such as Chakra UI), and data fetching/state tools like React Query. 
• Understanding of responsive design and cross-platform considerations.
• Strong communication skills and the ability to collaborate effectively with cross-functional teams.
• Experience with, or openness to, using modern AI-assisted tools for coding, documentation, debugging, and exploration.
• Curiosity, a continuous learning mindset, and a willingness to experiment with new technologies.
• Experience with eCommerce, headless commerce, or retail POS/OMS systems is an asset but not required.
• English proficiency is required. 

Is the Role a Fit for You?

You’ll thrive as an Intermediate Developer at Orium if:

• You enjoy building high-quality software and seeing your work come to life.
• You’re eager to deepen your expertise and learn from senior engineers.
• You’re collaborative, curious, and energized by problem-solving.
• You’re excited to use AI-powered tools to boost your workflow, not replace your judgment.
• You like finding ways to automate repetitive tasks and improve processes.
• You value team success and shared ownership over individual heroics.

Benefits and Perks

• Flexible schedule of full-time hours with a remote-first setup—focus on results, not where you work.
• Ongoing opportunities for professional development, including certifications, conferences, and in-house mentorship.
• Benefits required by Mexican law, in full compliance with local regulations
• Benefits above the law to support your well-being and quality of life 

Compensation and Hiring Transparency 

• Expected Compensation (Mexico): Compensation will be offered in MXN, aligned with local market benchmarks and the employment model. Final compensation will consider experience, skills, location, internal equity, and business needs.
• Use of AI in Hiring: To keep the process efficient and focused on human connection, we use AI-enabled and automated tools for tasks like candidate communications and scheduling, interview note-taking, and summarizing feedback for hiring teams. Our recruiters and hiring managers review all information, and humans make every hiring decision.
• Vacancy Status: This posting is for an existing vacancy we are actively hiring for.

Performance and Growth Expectations

We emphasize accountability for outcomes, but autonomy in activities. Your work will be measured across a number of data points (peer, leader & project team feedback) and will also be measured on the basis of client and user satisfaction. Your growth path is in your hands— you’ll have ongoing meetings with your leader to help determine your path, but your progress will be based on what you hope to achieve and how you choose to access the resources available to you.

Committed to an Inclusive Workplace

We are committed to fostering an inclusive and accessible workplace. We provide reasonable accommodations throughout the hiring process in accordance with applicable local laws. If you require accommodations, we will work with you to meet your needs.

Committed to Social and Environmental Stewardship

Orium is committed to promoting and working towards a more socially and environmentally sustainable future. All employees are expected to make decisions and take actions in relation to their role and work that follow through on this commitment.

#LI-Remote

Role Description

Responsibilities

• Help define company data assets (data model), Spark, SparkSQL jobs to populate data models
• Help define and design data integrations, data quality frameworks and design and evaluate open source/vendor tools for data lineage
• Work closely with Dropbox business units and engineering teams to develop strategy for long term Data Platform architecture to be efficient, reliable and scalable 
• Conceptualize and own the data architecture for multiple large-scale projects, while evaluating design and operational cost-benefit tradeoffs within systems
• Collaborate with engineers, product managers, and data scientists to understand data needs, representing key data insights in a meaningful way
• Design, build, and launch collections of sophisticated data models and visualizations that support multiple use cases across different products or domains
• Optimize pipelines, dashboards, frameworks, and systems to facilitate easier development of data artifacts

Many teams at Dropbox run Services with on-call rotations, which entails being available for calls during both core and non-core business hours. If a team has an on-call rotation, all engineers on the team are expected to participate in the rotation as part of their employment. Applicants are encouraged to ask for more details of the rotations to which the applicant is applying.

Requirements

• 5+ years of Spark, Python, Java, C++, or Scala development experience
• 5+ years of SQL experience
• 5+ years of experience with schema design, dimensional data modeling, and medallion architectures
• Experience with the Databricks platform and data lake architectures for large-scale data processing and analytics
• Excellent product strategic thinking and communications to influence product and cross-functional teams by identifying the data opportunities to drive impact
• BS degree in Computer Science or related technical field involving coding (e.g., physics or mathematics), or equivalent technical experience
• Experience designing, building and maintaining data processing systems

Role Description

Responsibilities

• Help define company data assets (data model), Spark, SparkSQL jobs to populate data models
• Help define and design data integrations, data quality frameworks and design and evaluate open source/vendor tools for data lineage
• Work closely with Dropbox business units and engineering teams to develop strategy for long term Data Platform architecture to be efficient, reliable and scalable 
• Conceptualize and own the data architecture for multiple large-scale projects, while evaluating design and operational cost-benefit tradeoffs within systems
• Collaborate with engineers, product managers, and data scientists to understand data needs, representing key data insights in a meaningful way
• Design, build, and launch collections of sophisticated data models and visualizations that support multiple use cases across different products or domains
• Optimize pipelines, dashboards, frameworks, and systems to facilitate easier development of data artifacts

Many teams at Dropbox run Services with on-call rotations, which entails being available for calls during both core and non-core business hours. If a team has an on-call rotation, all engineers on the team are expected to participate in the rotation as part of their employment. Applicants are encouraged to ask for more details of the rotations to which the applicant is applying.

Requirements

• 5+ years of Spark, Python, Java, C++, or Scala development experience
• 5+ years of SQL experience
• 5+ years of experience with schema design, dimensional data modeling, and medallion architectures
• Experience with the Databricks platform and data lake architectures for large-scale data processing and analytics
• Excellent product strategic thinking and communications to influence product and cross-functional teams by identifying the data opportunities to drive impact
• BS degree in Computer Science or related technical field involving coding (e.g., physics or mathematics), or equivalent technical experience
• Experience designing, building and maintaining data processing systems

Role Description

Dropbox is looking for a Staff Data Engineer to join our Analytics Data Engineering (ADE) team within Data Science & AI Platform. You will be responsible for solving cross-cutting data challenges that span multiple lines of business while driving standardization in how we build, deploy, and govern analytics pipelines across Dropbox.

This is not a maintenance role. We are modernizing our analytics platform, upgrading orchestration infrastructure, building shared and reusable data models with conformed dimensions, establishing a certified metrics framework, and laying the foundation for AI-native data development. You will partner closely with Data Science, Data Infrastructure, Product Engineering, and Business Intelligence teams to make this happen.

You will play a crucial role in establishing analytics engineering standards, designing scalable data models, and driving cross-functional alignment on data governance. You will get substantial exposure to senior leadership, shape the technical direction of analytics infrastructure at Dropbox, and directly influence how data powers product and business decisions.

Responsibilities

• Lead the design and implementation of shared, reusable data models, defining shared fact tables, conformed dimensions, and a semantic/metrics layer that serves as the single source of truth across analytics functions
• Drive standardization of data engineering practices across ADE and functional analytics teams, including pipeline patterns, CI/CD workflows, naming conventions, and data modeling standards
• Partner with Data Infrastructure to modernize orchestration, improve pipeline decomposition, and establish secure dev/test environments with production data access
• Architect and implement a shift-left data governance strategy,  working with upstream data producers to establish data contracts, SLOs, and code-enforced quality gates that catch issues before production
• Collaborate with Data Science leads and Product Management to translate metric definitions into reliable, certified data pipelines that power executive dashboards, WBR reporting, and growth measurement
• Reduce operational burden by improving pipeline granularity, observability, and failure recovery, establishing runbooks and alerting standards that make on-call sustainable
• Evaluate and integrate AI-native tooling into the data development lifecycle, enabling conversational data exploration with guardrails and AI-assisted pipeline development

On-call work may be necessary occasionally to help address bugs, outages, or other operational issues, with the goal of maintaining a stable and high-quality experience for our customers.

Requirements

• BS degree in Computer Science or related technical field, or equivalent technical experience
• 12+ years of experience in data engineering or analytics engineering with increasing scope and technical leadership
• 12+ years of SQL experience, including complex analytical queries, window functions, and performance optimization at scale (Spark SQL)
• 8+ years of Python development experience, including building and maintaining production data pipelines
• Deep expertise in dimensional data modeling, schema design, and scalable data architecture, with hands-on experience building shared data models across multiple business domains
• Strong experience with orchestration tools (Airflow strongly preferred) and dbt, including pipeline design, scheduling strategies, and failure recovery patterns
• Demonstrated ability to drive cross-team technical alignment, establishing standards, influencing without authority, and working across Data Engineering, Data Science, Data Infrastructure, and Product Engineering boundaries

Preferred Qualifications

• Experience with Databricks (Unity Catalog, Delta Lake) and modern lakehouse architectures
• Experience leading orchestration or platform modernization efforts at scale
• Familiarity with data governance and observability tools such as Atlan, Monte Carlo, Great Expectations, or similar
• Experience building or contributing to a metrics/semantic layer (dbt MetricFlow, Databricks Metric Views, or equivalent)
• Track record of establishing data engineering standards and best practices in a federated analytics organization

Role Description

Dropbox is looking for a Data Engineer to join our Analytics Data Engineering (ADE) team within Data Science & AI Platform. In this role you will build large, scalable analytics pipelines using modern data technologies. This is not a “maintain existing platform” or “make minor tweaks to current code base” kind of role. We are effectively building from the ground up and plan to leverage the most recent Big Data technologies. If you enjoy building new things without being constrained by technical debt, this is the job for you!

Responsibilities

• Define company data assets (data model), Spark, SparkSQL jobs to populate data models
• Define and design data integrations, data quality frameworks and design and evaluate open source/vendor tools for data lineage
• Work closely with Dropbox business units and engineering teams to develop strategy for long term Data Platform architecture to be efficient, reliable and scalable 
• Conceptualize and own the data architecture for multiple large-scale projects, while evaluating design and operational cost-benefit tradeoffs within systems
• Collaborate with engineers, product managers, and data scientists to understand data needs, representing key data insights in a meaningful way
• Design, build, and launch collections of sophisticated data models and visualizations that support multiple use cases across different products or domains
• Optimize pipelines, dashboards, frameworks, and systems to facilitate easier development of data artifacts

On-call work may be necessary occasionally to help address bugs, outages, or other operational issues, with the goal of maintaining a stable and high-quality experience for our customers.

Requirements

• 5+ years of Spark, Python, Java, C++, or Scala development experience
• 5+ years of SQL experience
• 5+ years of experience with schema design, dimensional data modeling, and medallion architectures
• Experience with the Databricks platform and data lake architectures for large-scale data processing and analytics
• Excellent product strategic thinking and communications to influence product and cross-functional teams by identifying the data opportunities to drive impact
• BS degree in Computer Science or related technical field involving coding (e.g., physics or mathematics), or equivalent technical experience
• Experience designing, building and maintaining data processing systems

Preferred Qualifications

• 7+ years of SQL experience 
• 7+ years of experience with schema design, dimensional data modeling, and medallion architectures
• Experience with Airflow or other similar orchestration frameworks
• Experience building data quality monitoring using MonteCarlo or similar tools

Role Description

Dropbox is looking for a Staff Data Engineer to join our Analytics Data Engineering (ADE) team within Data Science & AI Platform. You will be responsible for solving cross-cutting data challenges that span multiple lines of business while driving standardization in how we build, deploy, and govern analytics pipelines across Dropbox.

This is not a maintenance role. We are modernizing our analytics platform, upgrading orchestration infrastructure, building shared and reusable data models with conformed dimensions, establishing a certified metrics framework, and laying the foundation for AI-native data development. You will partner closely with Data Science, Data Infrastructure, Product Engineering, and Business Intelligence teams to make this happen.

You will play a crucial role in establishing analytics engineering standards, designing scalable data models, and driving cross-functional alignment on data governance. You will get substantial exposure to senior leadership, shape the technical direction of analytics infrastructure at Dropbox, and directly influence how data powers product and business decisions.

Our Engineering Career Framework is viewable by anyone outside the company and describes what’s expected for our engineers at each of our career levels. Check out our blog post on this topic and more here.

Responsibilities

• Lead the design and implementation of shared, reusable data models, defining shared fact tables, conformed dimensions, and a semantic/metrics layer that serves as the single source of truth across analytics functions
• Drive standardization of data engineering practices across ADE and functional analytics teams, including pipeline patterns, CI/CD workflows, naming conventions, and data modeling standards
• Partner with Data Infrastructure to modernize orchestration, improve pipeline decomposition, and establish secure dev/test environments with production data access
• Architect and implement a shift-left data governance strategy,  working with upstream data producers to establish data contracts, SLOs, and code-enforced quality gates that catch issues before production
• Collaborate with Data Science leads and Product Management to translate metric definitions into reliable, certified data pipelines that power executive dashboards, WBR reporting, and growth measurement
• Reduce operational burden by improving pipeline granularity, observability, and failure recovery, establishing runbooks and alerting standards that make on-call sustainable
• Evaluate and integrate AI-native tooling into the data development lifecycle, enabling conversational data exploration with guardrails and AI-assisted pipeline development

Many teams at Dropbox run Services with on-call rotations, which entails being available for calls during both core and non-core business hours. If a team has an on-call rotation, all engineers on the team are expected to participate in the rotation as part of their employment. Applicants are encouraged to ask for more details of the rotations to which the applicant is applying.

Requirements

• BS degree in Computer Science or related technical field, or equivalent technical experience
• 12+ years of experience in data engineering or analytics engineering with increasing scope and technical leadership
• 12+ years of SQL experience, including complex analytical queries, window functions, and performance optimization at scale (Spark SQL)
• 8+ years of Python development experience, including building and maintaining production data pipelines
• Deep expertise in dimensional data modeling, schema design, and scalable data architecture, with hands-on experience building shared data models across multiple business domains
• Strong experience with orchestration tools (Airflow strongly preferred) and dbt, including pipeline design, scheduling strategies, and failure recovery patterns
• Demonstrated ability to drive cross-team technical alignment, establishing standards, influencing without authority, and working across Data Engineering, Data Science, Data Infrastructure, and Product Engineering boundaries

Preferred Qualifications

• Experience with Databricks (Unity Catalog, Delta Lake) and modern lakehouse architectures
• Experience leading orchestration or platform modernization efforts at scale
• Familiarity with data governance and observability tools such as Atlan, Monte Carlo, Great Expectations, or similar
• Experience building or contributing to a metrics/semantic layer (dbt MetricFlow, Databricks Metric Views, or equivalent)
• Track record of establishing data engineering standards and best practices in a federated analytics organization

Compensation

Role Description

Dropbox is looking for a Staff Data Engineer to join our Analytics Data Engineering (ADE) team within Data Science & AI Platform. You will be responsible for solving cross-cutting data challenges that span multiple lines of business while driving standardization in how we build, deploy, and govern analytics pipelines across Dropbox.

This is not a maintenance role. We are modernizing our analytics platform, upgrading orchestration infrastructure, building shared and reusable data models with conformed dimensions, establishing a certified metrics framework, and laying the foundation for AI-native data development. You will partner closely with Data Science, Data Infrastructure, Product Engineering, and Business Intelligence teams to make this happen.

You will play a crucial role in establishing analytics engineering standards, designing scalable data models, and driving cross-functional alignment on data governance. You will get substantial exposure to senior leadership, shape the technical direction of analytics infrastructure at Dropbox, and directly influence how data powers product and business decisions.

Our Engineering Career Framework is viewable by anyone outside the company and describes what’s expected for our engineers at each of our career levels. Check out our blog post on this topic and more here.

Responsibilities

• Lead the design and implementation of shared, reusable data models, defining shared fact tables, conformed dimensions, and a semantic/metrics layer that serves as the single source of truth across analytics functions
• Drive standardization of data engineering practices across ADE and functional analytics teams, including pipeline patterns, CI/CD workflows, naming conventions, and data modeling standards
• Partner with Data Infrastructure to modernize orchestration, improve pipeline decomposition, and establish secure dev/test environments with production data access
• Architect and implement a shift-left data governance strategy,  working with upstream data producers to establish data contracts, SLOs, and code-enforced quality gates that catch issues before production
• Collaborate with Data Science leads and Product Management to translate metric definitions into reliable, certified data pipelines that power executive dashboards, WBR reporting, and growth measurement
• Reduce operational burden by improving pipeline granularity, observability, and failure recovery, establishing runbooks and alerting standards that make on-call sustainable
• Evaluate and integrate AI-native tooling into the data development lifecycle, enabling conversational data exploration with guardrails and AI-assisted pipeline development

Many teams at Dropbox run Services with on-call rotations, which entails being available for calls during both core and non-core business hours. If a team has an on-call rotation, all engineers on the team are expected to participate in the rotation as part of their employment. Applicants are encouraged to ask for more details of the rotations to which the applicant is applying.

Requirements

• BS degree in Computer Science or related technical field, or equivalent technical experience
• 12+ years of experience in data engineering or analytics engineering with increasing scope and technical leadership
• 12+ years of SQL experience, including complex analytical queries, window functions, and performance optimization at scale (Spark SQL)
• 8+ years of Python development experience, including building and maintaining production data pipelines
• Deep expertise in dimensional data modeling, schema design, and scalable data architecture, with hands-on experience building shared data models across multiple business domains
• Strong experience with orchestration tools (Airflow strongly preferred) and dbt, including pipeline design, scheduling strategies, and failure recovery patterns
• Demonstrated ability to drive cross-team technical alignment, establishing standards, influencing without authority, and working across Data Engineering, Data Science, Data Infrastructure, and Product Engineering boundaries

Preferred Qualifications

• Experience with Databricks (Unity Catalog, Delta Lake) and modern lakehouse architectures
• Experience leading orchestration or platform modernization efforts at scale
• Familiarity with data governance and observability tools such as Atlan, Monte Carlo, Great Expectations, or similar
• Experience building or contributing to a metrics/semantic layer (dbt MetricFlow, Databricks Metric Views, or equivalent)
• Track record of establishing data engineering standards and best practices in a federated analytics organization

Compensation

Important Information

Experience: +6 years

Job Mode: Full-time

Work Mode: Remote

ID: 21204

Job Summary

We are seeking a highly skilled Data Quality / Data Governance Specialist with a strong focus on execution and implementation, not just documentation. This role is critical in ensuring data reliability, integrity, and governance across both batch and real-time data ecosystems.

You will work closely with data engineering, analytics, and business teams to operationalize data governance frameworks, enforce data quality standards, and implement observability practices across modern data platforms.

Responsibilities and Duties

Data Governance & Execution

• Implement and operationalize data governance frameworks, policies, and standards across the organization.
• Move beyond documentation to ensure real enforcement of governance practices within data pipelines and systems.
• Define and enforce data contracts between producers and consumers.
• Establish ownership, stewardship, and accountability models for data assets.

Data Quality & Observability

• Design and implement data quality frameworks to ensure accuracy, completeness, and consistency of data.
• Define and monitor data quality rules and SLAs across datasets.
• Implement and manage data observability tools to track data health, lineage, and anomalies.
• Partner with engineering teams to integrate quality checks into pipelines.

Data Architecture (Batch & Real-Time)

• Ensure data quality and governance across:
  • Batch processing architectures (e.g., Medallion architecture: Bronze, Silver, Gold layers)
  • Real-time/streaming systems
• Implement validation and quality checks across all layers of the data lifecycle.
• Collaborate on architecture decisions to embed governance and quality by design.

Modern Data Stack Implementation

• Work hands-on with modern data technologies, including:
  • Python, SQL, Spark for data processing and validation
  • AWS services such as Kinesis, Lambda, SQS/SNS
  • Data lake/table formats such as Apache Iceberg
• Integrate governance and quality controls into data pipelines and workflows.

Collaboration & Continuous Improvement

• Collaborate with Data Engineers, Data Scientists, and Business stakeholders to ensure trusted data usage.
• Educate teams on data governance best practices and standards.
• Continuously identify opportunities to improve data reliability, reduce incidents, and increase trust in data.
• Support incident resolution related to data quality issues and implement preventive measures.

Qualifications and Skills

• 5+ years of experience in Data Governance, Data Quality, or Data Engineering-related roles.
• Proven experience implementing (not just documenting) data governance frameworks.
• Strong hands-on experience with:
  • Data quality frameworks and validation strategies
  • Data contracts and schema enforcement
  • Data observability tools and practices
• Experience working with:
  • Batch architectures (Medallion architecture preferred)
  • Real-time/streaming data pipelines
• Proficiency in:
  • SQL and Python
  • Distributed data processing tools such as Spark
• Experience with modern data stack technologies:
  • AWS (Kinesis, Lambda, SQS/SNS)
  • Apache Iceberg or similar table formats

Preferred Qualifications 

• Experience with tools like Great Expectations, Monte Carlo, Databand, or similar observability platforms.
• Familiarity with data cataloging and lineage tools.
• Knowledge of data privacy, compliance, and regulatory frameworks.
• Experience with CI/CD integration for data pipelines.
• Strong understanding of data modeling and data architecture patterns.

About Encora 

Encora is a global company that offers Software and Digital Engineering solutions. Our practices include Cloud Services, Product Engineering & Application Modernization, Data & Analytics, Digital Experience & Design Services, DevSecOps, Cybersecurity, Quality Engineering, AI & LLM Engineering, among others. 

At Encora, we hire professionals based solely on their skills and do not discriminate based on age, disability, religion, gender, sexual orientation, socioeconomic status, or nationality. 

MUST HAVE:

• 5+ years of experience in data engineering within fast-paced, cloud-native environments
• Deep expertise in Python, SQL, Docker, and AWS (S3, Glue, Kinesis, Athena/Presto)
• Experience building and managing scalable ETL pipelines and data lake infrastructure
• Familiarity with distributed systems, Spark, and data quality best practices
• Strong cross-functional collaboration skills to support BI, analytics, and engineering teams

EXPERIENCE: 5+ years of data engineering experience in an AWS-based environment where data powers decision-making across product, marketing, and operations.

YOUR ROLE

Lead scalable data engineering efforts that empower cross-functional teams with reliable, timely, and actionable data, ensuring Launch Potato’s analytics and business intelligence infrastructure fuels strategic growth.

OUTCOMES

• Build and optimize scalable, efficient ETL and data lake processes that proactively catch issues before they impact the business
• Own the ingestion, modeling, and transformation of structured and unstructured data to support reporting and analysis across all business units
• Partner closely with BI and Analytics to deliver clean, query-ready datasets that improve user acquisition, engagement, and revenue growth
• Maintain and enhance database monitoring, anomaly detection, and quality assurance workflows
• Serve as the internal point of contact for reporting infrastructure—delivering ad hoc data analyses and driving consistent data integrity
• Drive adoption and advancement of Looker dashboards by ensuring robust and scalable backend data support
• Contribute to the future of Launch Potato’s data team by mentoring peers and shaping a high-performance, quality-first engineering culture

COMPETENCIES

• Data Engineering Mastery: Demonstrates technical excellence in building data pipelines, troubleshooting distributed systems, and scaling infrastructure using AWS and open-source tools
• Cross-Functional Collaboration: Communicates clearly across technical and non-technical teams, translating business needs into robust data solutions
• Proactive Ownership: Operates with a strong sense of accountability; identifies and solves data issues independently and efficiently
• Quality-Driven Execution: Holds a high bar for data accuracy, auditability, and documentation throughout all systems and workflows
• Strategic Thinking: Anticipates how data infrastructure impacts wider company OKRs and proactively suggests improvements and innovations
• Growth Mindset: Seeks out opportunities to elevate team capabilities, mentor others, and stay ahead of evolving best practices in data engineering

MUST HAVE:

• 5+ years of experience in data engineering within fast-paced, cloud-native environments
• Deep expertise in Python, SQL, Docker, and AWS (S3, Glue, Kinesis, Athena/Presto)
• Experience building and managing scalable ETL pipelines and data lake infrastructure
• Familiarity with distributed systems, Spark, and data quality best practices
• Strong cross-functional collaboration skills to support BI, analytics, and engineering teams

EXPERIENCE: 5+ years of data engineering experience in an AWS-based environment where data powers decision-making across product, marketing, and operations.

YOUR ROLE

Lead scalable data engineering efforts that empower cross-functional teams with reliable, timely, and actionable data, ensuring Launch Potato’s analytics and business intelligence infrastructure fuels strategic growth.

OUTCOMES

• Build and optimize scalable, efficient ETL and data lake processes that proactively catch issues before they impact the business
• Own the ingestion, modeling, and transformation of structured and unstructured data to support reporting and analysis across all business units
• Partner closely with BI and Analytics to deliver clean, query-ready datasets that improve user acquisition, engagement, and revenue growth
• Maintain and enhance database monitoring, anomaly detection, and quality assurance workflows
• Serve as the internal point of contact for reporting infrastructure—delivering ad hoc data analyses and driving consistent data integrity
• Drive adoption and advancement of Looker dashboards by ensuring robust and scalable backend data support
• Contribute to the future of Launch Potato’s data team by mentoring peers and shaping a high-performance, quality-first engineering culture

COMPETENCIES

• Data Engineering Mastery: Demonstrates technical excellence in building data pipelines, troubleshooting distributed systems, and scaling infrastructure using AWS and open-source tools
• Cross-Functional Collaboration: Communicates clearly across technical and non-technical teams, translating business needs into robust data solutions
• Proactive Ownership: Operates with a strong sense of accountability; identifies and solves data issues independently and efficiently
• Quality-Driven Execution: Holds a high bar for data accuracy, auditability, and documentation throughout all systems and workflows
• Strategic Thinking: Anticipates how data infrastructure impacts wider company OKRs and proactively suggests improvements and innovations
• Growth Mindset: Seeks out opportunities to elevate team capabilities, mentor others, and stay ahead of evolving best practices in data engineering

MUST HAVE:

• 5+ years of experience in data engineering within fast-paced, cloud-native environments
• Deep expertise in Python, SQL, Docker, and AWS (S3, Glue, Kinesis, Athena/Presto)
• Experience building and managing scalable ETL pipelines and data lake infrastructure
• Familiarity with distributed systems, Spark, and data quality best practices
• Strong cross-functional collaboration skills to support BI, analytics, and engineering teams

EXPERIENCE: 5+ years of data engineering experience in an AWS-based environment where data powers decision-making across product, marketing, and operations.

YOUR ROLE

Lead scalable data engineering efforts that empower cross-functional teams with reliable, timely, and actionable data, ensuring Launch Potato’s analytics and business intelligence infrastructure fuels strategic growth.

OUTCOMES

• Build and optimize scalable, efficient ETL and data lake processes that proactively catch issues before they impact the business
• Own the ingestion, modeling, and transformation of structured and unstructured data to support reporting and analysis across all business units
• Partner closely with BI and Analytics to deliver clean, query-ready datasets that improve user acquisition, engagement, and revenue growth
• Maintain and enhance database monitoring, anomaly detection, and quality assurance workflows
• Serve as the internal point of contact for reporting infrastructure—delivering ad hoc data analyses and driving consistent data integrity
• Drive adoption and advancement of Looker dashboards by ensuring robust and scalable backend data support
• Contribute to the future of Launch Potato’s data team by mentoring peers and shaping a high-performance, quality-first engineering culture

COMPETENCIES

• Data Engineering Mastery: Demonstrates technical excellence in building data pipelines, troubleshooting distributed systems, and scaling infrastructure using AWS and open-source tools
• Cross-Functional Collaboration: Communicates clearly across technical and non-technical teams, translating business needs into robust data solutions
• Proactive Ownership: Operates with a strong sense of accountability; identifies and solves data issues independently and efficiently
• Quality-Driven Execution: Holds a high bar for data accuracy, auditability, and documentation throughout all systems and workflows
• Strategic Thinking: Anticipates how data infrastructure impacts wider company OKRs and proactively suggests improvements and innovations
• Growth Mindset: Seeks out opportunities to elevate team capabilities, mentor others, and stay ahead of evolving best practices in data engineering

MUST HAVE:

• 5+ years of experience in data engineering within fast-paced, cloud-native environments
• Deep expertise in Python, SQL, Docker, and AWS (S3, Glue, Kinesis, Athena/Presto)
• Experience building and managing scalable ETL pipelines and data lake infrastructure
• Familiarity with distributed systems, Spark, and data quality best practices
• Strong cross-functional collaboration skills to support BI, analytics, and engineering teams

EXPERIENCE: 5+ years of data engineering experience in an AWS-based environment where data powers decision-making across product, marketing, and operations.

YOUR ROLE

Lead scalable data engineering efforts that empower cross-functional teams with reliable, timely, and actionable data, ensuring Launch Potato’s analytics and business intelligence infrastructure fuels strategic growth.

OUTCOMES

• Build and optimize scalable, efficient ETL and data lake processes that proactively catch issues before they impact the business
• Own the ingestion, modeling, and transformation of structured and unstructured data to support reporting and analysis across all business units
• Partner closely with BI and Analytics to deliver clean, query-ready datasets that improve user acquisition, engagement, and revenue growth
• Maintain and enhance database monitoring, anomaly detection, and quality assurance workflows
• Serve as the internal point of contact for reporting infrastructure—delivering ad hoc data analyses and driving consistent data integrity
• Drive adoption and advancement of Looker dashboards by ensuring robust and scalable backend data support
• Contribute to the future of Launch Potato’s data team by mentoring peers and shaping a high-performance, quality-first engineering culture

COMPETENCIES

• Data Engineering Mastery: Demonstrates technical excellence in building data pipelines, troubleshooting distributed systems, and scaling infrastructure using AWS and open-source tools
• Cross-Functional Collaboration: Communicates clearly across technical and non-technical teams, translating business needs into robust data solutions
• Proactive Ownership: Operates with a strong sense of accountability; identifies and solves data issues independently and efficiently
• Quality-Driven Execution: Holds a high bar for data accuracy, auditability, and documentation throughout all systems and workflows
• Strategic Thinking: Anticipates how data infrastructure impacts wider company OKRs and proactively suggests improvements and innovations
• Growth Mindset: Seeks out opportunities to elevate team capabilities, mentor others, and stay ahead of evolving best practices in data engineering

MUST HAVE:

• 5+ years of experience in data engineering within fast-paced, cloud-native environments
• Deep expertise in Python, SQL, Docker, and AWS (S3, Glue, Kinesis, Athena/Presto)
• Experience building and managing scalable ETL pipelines and data lake infrastructure
• Familiarity with distributed systems, Spark, and data quality best practices
• Strong cross-functional collaboration skills to support BI, analytics, and engineering teams

EXPERIENCE: 5+ years of data engineering experience in an AWS-based environment where data powers decision-making across product, marketing, and operations.

YOUR ROLE

Lead scalable data engineering efforts that empower cross-functional teams with reliable, timely, and actionable data, ensuring Launch Potato’s analytics and business intelligence infrastructure fuels strategic growth.

OUTCOMES

• Build and optimize scalable, efficient ETL and data lake processes that proactively catch issues before they impact the business
• Own the ingestion, modeling, and transformation of structured and unstructured data to support reporting and analysis across all business units
• Partner closely with BI and Analytics to deliver clean, query-ready datasets that improve user acquisition, engagement, and revenue growth
• Maintain and enhance database monitoring, anomaly detection, and quality assurance workflows
• Serve as the internal point of contact for reporting infrastructure—delivering ad hoc data analyses and driving consistent data integrity
• Drive adoption and advancement of Looker dashboards by ensuring robust and scalable backend data support
• Contribute to the future of Launch Potato’s data team by mentoring peers and shaping a high-performance, quality-first engineering culture

COMPETENCIES

• Data Engineering Mastery: Demonstrates technical excellence in building data pipelines, troubleshooting distributed systems, and scaling infrastructure using AWS and open-source tools
• Cross-Functional Collaboration: Communicates clearly across technical and non-technical teams, translating business needs into robust data solutions
• Proactive Ownership: Operates with a strong sense of accountability; identifies and solves data issues independently and efficiently
• Quality-Driven Execution: Holds a high bar for data accuracy, auditability, and documentation throughout all systems and workflows
• Strategic Thinking: Anticipates how data infrastructure impacts wider company OKRs and proactively suggests improvements and innovations
• Growth Mindset: Seeks out opportunities to elevate team capabilities, mentor others, and stay ahead of evolving best practices in data engineering

MUST HAVE:

• 5+ years of experience in data engineering within fast-paced, cloud-native environments
• Deep expertise in Python, SQL, Docker, and AWS (S3, Glue, Kinesis, Athena/Presto)
• Experience building and managing scalable ETL pipelines and data lake infrastructure
• Familiarity with distributed systems, Spark, and data quality best practices
• Strong cross-functional collaboration skills to support BI, analytics, and engineering teams

EXPERIENCE: 5+ years of data engineering experience in an AWS-based environment where data powers decision-making across product, marketing, and operations.

YOUR ROLE

Lead scalable data engineering efforts that empower cross-functional teams with reliable, timely, and actionable data, ensuring Launch Potato’s analytics and business intelligence infrastructure fuels strategic growth.

OUTCOMES

• Build and optimize scalable, efficient ETL and data lake processes that proactively catch issues before they impact the business
• Own the ingestion, modeling, and transformation of structured and unstructured data to support reporting and analysis across all business units
• Partner closely with BI and Analytics to deliver clean, query-ready datasets that improve user acquisition, engagement, and revenue growth
• Maintain and enhance database monitoring, anomaly detection, and quality assurance workflows
• Serve as the internal point of contact for reporting infrastructure—delivering ad hoc data analyses and driving consistent data integrity
• Drive adoption and advancement of Looker dashboards by ensuring robust and scalable backend data support
• Contribute to the future of Launch Potato’s data team by mentoring peers and shaping a high-performance, quality-first engineering culture

COMPETENCIES

• Data Engineering Mastery: Demonstrates technical excellence in building data pipelines, troubleshooting distributed systems, and scaling infrastructure using AWS and open-source tools
• Cross-Functional Collaboration: Communicates clearly across technical and non-technical teams, translating business needs into robust data solutions
• Proactive Ownership: Operates with a strong sense of accountability; identifies and solves data issues independently and efficiently
• Quality-Driven Execution: Holds a high bar for data accuracy, auditability, and documentation throughout all systems and workflows
• Strategic Thinking: Anticipates how data infrastructure impacts wider company OKRs and proactively suggests improvements and innovations
• Growth Mindset: Seeks out opportunities to elevate team capabilities, mentor others, and stay ahead of evolving best practices in data engineering

MUST HAVE:

• 5+ years of experience in data engineering within fast-paced, cloud-native environments
• Deep expertise in Python, SQL, Docker, and AWS (S3, Glue, Kinesis, Athena/Presto)
• Experience building and managing scalable ETL pipelines and data lake infrastructure
• Familiarity with distributed systems, Spark, and data quality best practices
• Strong cross-functional collaboration skills to support BI, analytics, and engineering teams

EXPERIENCE: 5+ years of data engineering experience in an AWS-based environment where data powers decision-making across product, marketing, and operations.

YOUR ROLE

Lead scalable data engineering efforts that empower cross-functional teams with reliable, timely, and actionable data, ensuring Launch Potato’s analytics and business intelligence infrastructure fuels strategic growth.

OUTCOMES

• Build and optimize scalable, efficient ETL and data lake processes that proactively catch issues before they impact the business
• Own the ingestion, modeling, and transformation of structured and unstructured data to support reporting and analysis across all business units
• Partner closely with BI and Analytics to deliver clean, query-ready datasets that improve user acquisition, engagement, and revenue growth
• Maintain and enhance database monitoring, anomaly detection, and quality assurance workflows
• Serve as the internal point of contact for reporting infrastructure—delivering ad hoc data analyses and driving consistent data integrity
• Drive adoption and advancement of Looker dashboards by ensuring robust and scalable backend data support
• Contribute to the future of Launch Potato’s data team by mentoring peers and shaping a high-performance, quality-first engineering culture

COMPETENCIES

• Data Engineering Mastery: Demonstrates technical excellence in building data pipelines, troubleshooting distributed systems, and scaling infrastructure using AWS and open-source tools
• Cross-Functional Collaboration: Communicates clearly across technical and non-technical teams, translating business needs into robust data solutions
• Proactive Ownership: Operates with a strong sense of accountability; identifies and solves data issues independently and efficiently
• Quality-Driven Execution: Holds a high bar for data accuracy, auditability, and documentation throughout all systems and workflows
• Strategic Thinking: Anticipates how data infrastructure impacts wider company OKRs and proactively suggests improvements and innovations
• Growth Mindset: Seeks out opportunities to elevate team capabilities, mentor others, and stay ahead of evolving best practices in data engineering

MUST HAVE:

• 5+ years of experience in data engineering within fast-paced, cloud-native environments
• Deep expertise in Python, SQL, Docker, and AWS (S3, Glue, Kinesis, Athena/Presto)
• Experience building and managing scalable ETL pipelines and data lake infrastructure
• Familiarity with distributed systems, Spark, and data quality best practices
• Strong cross-functional collaboration skills to support BI, analytics, and engineering teams

EXPERIENCE: 5+ years of data engineering experience in an AWS-based environment where data powers decision-making across product, marketing, and operations.

YOUR ROLE

Lead scalable data engineering efforts that empower cross-functional teams with reliable, timely, and actionable data, ensuring Launch Potato’s analytics and business intelligence infrastructure fuels strategic growth.

OUTCOMES

• Build and optimize scalable, efficient ETL and data lake processes that proactively catch issues before they impact the business
• Own the ingestion, modeling, and transformation of structured and unstructured data to support reporting and analysis across all business units
• Partner closely with BI and Analytics to deliver clean, query-ready datasets that improve user acquisition, engagement, and revenue growth
• Maintain and enhance database monitoring, anomaly detection, and quality assurance workflows
• Serve as the internal point of contact for reporting infrastructure—delivering ad hoc data analyses and driving consistent data integrity
• Drive adoption and advancement of Looker dashboards by ensuring robust and scalable backend data support
• Contribute to the future of Launch Potato’s data team by mentoring peers and shaping a high-performance, quality-first engineering culture

COMPETENCIES

• Data Engineering Mastery: Demonstrates technical excellence in building data pipelines, troubleshooting distributed systems, and scaling infrastructure using AWS and open-source tools
• Cross-Functional Collaboration: Communicates clearly across technical and non-technical teams, translating business needs into robust data solutions
• Proactive Ownership: Operates with a strong sense of accountability; identifies and solves data issues independently and efficiently
• Quality-Driven Execution: Holds a high bar for data accuracy, auditability, and documentation throughout all systems and workflows
• Strategic Thinking: Anticipates how data infrastructure impacts wider company OKRs and proactively suggests improvements and innovations
• Growth Mindset: Seeks out opportunities to elevate team capabilities, mentor others, and stay ahead of evolving best practices in data engineering

MUST HAVE:

• 5+ years of experience in data engineering within fast-paced, cloud-native environments
• Deep expertise in Python, SQL, Docker, and AWS (S3, Glue, Kinesis, Athena/Presto)
• Experience building and managing scalable ETL pipelines and data lake infrastructure
• Familiarity with distributed systems, Spark, and data quality best practices
• Strong cross-functional collaboration skills to support BI, analytics, and engineering teams

EXPERIENCE: 5+ years of data engineering experience in an AWS-based environment where data powers decision-making across product, marketing, and operations.

YOUR ROLE

Lead scalable data engineering efforts that empower cross-functional teams with reliable, timely, and actionable data, ensuring Launch Potato’s analytics and business intelligence infrastructure fuels strategic growth.

OUTCOMES

• Build and optimize scalable, efficient ETL and data lake processes that proactively catch issues before they impact the business
• Own the ingestion, modeling, and transformation of structured and unstructured data to support reporting and analysis across all business units
• Partner closely with BI and Analytics to deliver clean, query-ready datasets that improve user acquisition, engagement, and revenue growth
• Maintain and enhance database monitoring, anomaly detection, and quality assurance workflows
• Serve as the internal point of contact for reporting infrastructure—delivering ad hoc data analyses and driving consistent data integrity
• Drive adoption and advancement of Looker dashboards by ensuring robust and scalable backend data support
• Contribute to the future of Launch Potato’s data team by mentoring peers and shaping a high-performance, quality-first engineering culture

COMPETENCIES

• Data Engineering Mastery: Demonstrates technical excellence in building data pipelines, troubleshooting distributed systems, and scaling infrastructure using AWS and open-source tools
• Cross-Functional Collaboration: Communicates clearly across technical and non-technical teams, translating business needs into robust data solutions
• Proactive Ownership: Operates with a strong sense of accountability; identifies and solves data issues independently and efficiently
• Quality-Driven Execution: Holds a high bar for data accuracy, auditability, and documentation throughout all systems and workflows
• Strategic Thinking: Anticipates how data infrastructure impacts wider company OKRs and proactively suggests improvements and innovations
• Growth Mindset: Seeks out opportunities to elevate team capabilities, mentor others, and stay ahead of evolving best practices in data engineering

MUST HAVE:

• 5+ years of experience in data engineering within fast-paced, cloud-native environments
• Deep expertise in Python, SQL, Docker, and AWS (S3, Glue, Kinesis, Athena/Presto)
• Experience building and managing scalable ETL pipelines and data lake infrastructure
• Familiarity with distributed systems, Spark, and data quality best practices
• Strong cross-functional collaboration skills to support BI, analytics, and engineering teams

EXPERIENCE: 5+ years of data engineering experience in an AWS-based environment where data powers decision-making across product, marketing, and operations.

YOUR ROLE

Lead scalable data engineering efforts that empower cross-functional teams with reliable, timely, and actionable data, ensuring Launch Potato’s analytics and business intelligence infrastructure fuels strategic growth.

OUTCOMES

• Build and optimize scalable, efficient ETL and data lake processes that proactively catch issues before they impact the business
• Own the ingestion, modeling, and transformation of structured and unstructured data to support reporting and analysis across all business units
• Partner closely with BI and Analytics to deliver clean, query-ready datasets that improve user acquisition, engagement, and revenue growth
• Maintain and enhance database monitoring, anomaly detection, and quality assurance workflows
• Serve as the internal point of contact for reporting infrastructure—delivering ad hoc data analyses and driving consistent data integrity
• Drive adoption and advancement of Looker dashboards by ensuring robust and scalable backend data support
• Contribute to the future of Launch Potato’s data team by mentoring peers and shaping a high-performance, quality-first engineering culture

COMPETENCIES

• Data Engineering Mastery: Demonstrates technical excellence in building data pipelines, troubleshooting distributed systems, and scaling infrastructure using AWS and open-source tools
• Cross-Functional Collaboration: Communicates clearly across technical and non-technical teams, translating business needs into robust data solutions
• Proactive Ownership: Operates with a strong sense of accountability; identifies and solves data issues independently and efficiently
• Quality-Driven Execution: Holds a high bar for data accuracy, auditability, and documentation throughout all systems and workflows
• Strategic Thinking: Anticipates how data infrastructure impacts wider company OKRs and proactively suggests improvements and innovations
• Growth Mindset: Seeks out opportunities to elevate team capabilities, mentor others, and stay ahead of evolving best practices in data engineering

MUST HAVE:

• 5+ years of experience in data engineering within fast-paced, cloud-native environments
• Deep expertise in Python, SQL, Docker, and AWS (S3, Glue, Kinesis, Athena/Presto)
• Experience building and managing scalable ETL pipelines and data lake infrastructure
• Familiarity with distributed systems, Spark, and data quality best practices
• Strong cross-functional collaboration skills to support BI, analytics, and engineering teams

EXPERIENCE: 5+ years of data engineering experience in an AWS-based environment where data powers decision-making across product, marketing, and operations.

YOUR ROLE

Lead scalable data engineering efforts that empower cross-functional teams with reliable, timely, and actionable data, ensuring Launch Potato’s analytics and business intelligence infrastructure fuels strategic growth.

OUTCOMES

• Build and optimize scalable, efficient ETL and data lake processes that proactively catch issues before they impact the business
• Own the ingestion, modeling, and transformation of structured and unstructured data to support reporting and analysis across all business units
• Partner closely with BI and Analytics to deliver clean, query-ready datasets that improve user acquisition, engagement, and revenue growth
• Maintain and enhance database monitoring, anomaly detection, and quality assurance workflows
• Serve as the internal point of contact for reporting infrastructure—delivering ad hoc data analyses and driving consistent data integrity
• Drive adoption and advancement of Looker dashboards by ensuring robust and scalable backend data support
• Contribute to the future of Launch Potato’s data team by mentoring peers and shaping a high-performance, quality-first engineering culture

COMPETENCIES

• Data Engineering Mastery: Demonstrates technical excellence in building data pipelines, troubleshooting distributed systems, and scaling infrastructure using AWS and open-source tools
• Cross-Functional Collaboration: Communicates clearly across technical and non-technical teams, translating business needs into robust data solutions
• Proactive Ownership: Operates with a strong sense of accountability; identifies and solves data issues independently and efficiently
• Quality-Driven Execution: Holds a high bar for data accuracy, auditability, and documentation throughout all systems and workflows
• Strategic Thinking: Anticipates how data infrastructure impacts wider company OKRs and proactively suggests improvements and innovations
• Growth Mindset: Seeks out opportunities to elevate team capabilities, mentor others, and stay ahead of evolving best practices in data engineering

MUST HAVE:

• 5+ years of experience in data engineering within fast-paced, cloud-native environments
• Deep expertise in Python, SQL, Docker, and AWS (S3, Glue, Kinesis, Athena/Presto)
• Experience building and managing scalable ETL pipelines and data lake infrastructure
• Familiarity with distributed systems, Spark, and data quality best practices
• Strong cross-functional collaboration skills to support BI, analytics, and engineering teams

EXPERIENCE: 5+ years of data engineering experience in an AWS-based environment where data powers decision-making across product, marketing, and operations.

YOUR ROLE

Lead scalable data engineering efforts that empower cross-functional teams with reliable, timely, and actionable data, ensuring Launch Potato’s analytics and business intelligence infrastructure fuels strategic growth.

OUTCOMES

• Build and optimize scalable, efficient ETL and data lake processes that proactively catch issues before they impact the business
• Own the ingestion, modeling, and transformation of structured and unstructured data to support reporting and analysis across all business units
• Partner closely with BI and Analytics to deliver clean, query-ready datasets that improve user acquisition, engagement, and revenue growth
• Maintain and enhance database monitoring, anomaly detection, and quality assurance workflows
• Serve as the internal point of contact for reporting infrastructure—delivering ad hoc data analyses and driving consistent data integrity
• Drive adoption and advancement of Looker dashboards by ensuring robust and scalable backend data support
• Contribute to the future of Launch Potato’s data team by mentoring peers and shaping a high-performance, quality-first engineering culture

COMPETENCIES

• Data Engineering Mastery: Demonstrates technical excellence in building data pipelines, troubleshooting distributed systems, and scaling infrastructure using AWS and open-source tools
• Cross-Functional Collaboration: Communicates clearly across technical and non-technical teams, translating business needs into robust data solutions
• Proactive Ownership: Operates with a strong sense of accountability; identifies and solves data issues independently and efficiently
• Quality-Driven Execution: Holds a high bar for data accuracy, auditability, and documentation throughout all systems and workflows
• Strategic Thinking: Anticipates how data infrastructure impacts wider company OKRs and proactively suggests improvements and innovations
• Growth Mindset: Seeks out opportunities to elevate team capabilities, mentor others, and stay ahead of evolving best practices in data engineering

MUST HAVE:

• 5+ years of experience in data engineering within fast-paced, cloud-native environments
• Deep expertise in Python, SQL, Docker, and AWS (S3, Glue, Kinesis, Athena/Presto)
• Experience building and managing scalable ETL pipelines and data lake infrastructure
• Familiarity with distributed systems, Spark, and data quality best practices
• Strong cross-functional collaboration skills to support BI, analytics, and engineering teams

EXPERIENCE: 5+ years of data engineering experience in an AWS-based environment where data powers decision-making across product, marketing, and operations.

YOUR ROLE

Lead scalable data engineering efforts that empower cross-functional teams with reliable, timely, and actionable data, ensuring Launch Potato’s analytics and business intelligence infrastructure fuels strategic growth.

OUTCOMES

• Build and optimize scalable, efficient ETL and data lake processes that proactively catch issues before they impact the business
• Own the ingestion, modeling, and transformation of structured and unstructured data to support reporting and analysis across all business units
• Partner closely with BI and Analytics to deliver clean, query-ready datasets that improve user acquisition, engagement, and revenue growth
• Maintain and enhance database monitoring, anomaly detection, and quality assurance workflows
• Serve as the internal point of contact for reporting infrastructure—delivering ad hoc data analyses and driving consistent data integrity
• Drive adoption and advancement of Looker dashboards by ensuring robust and scalable backend data support
• Contribute to the future of Launch Potato’s data team by mentoring peers and shaping a high-performance, quality-first engineering culture

COMPETENCIES

• Data Engineering Mastery: Demonstrates technical excellence in building data pipelines, troubleshooting distributed systems, and scaling infrastructure using AWS and open-source tools
• Cross-Functional Collaboration: Communicates clearly across technical and non-technical teams, translating business needs into robust data solutions
• Proactive Ownership: Operates with a strong sense of accountability; identifies and solves data issues independently and efficiently
• Quality-Driven Execution: Holds a high bar for data accuracy, auditability, and documentation throughout all systems and workflows
• Strategic Thinking: Anticipates how data infrastructure impacts wider company OKRs and proactively suggests improvements and innovations
• Growth Mindset: Seeks out opportunities to elevate team capabilities, mentor others, and stay ahead of evolving best practices in data engineering

MUST HAVE:

• 5+ years of experience in data engineering within fast-paced, cloud-native environments
• Deep expertise in Python, SQL, Docker, and AWS (S3, Glue, Kinesis, Athena/Presto)
• Experience building and managing scalable ETL pipelines and data lake infrastructure
• Familiarity with distributed systems, Spark, and data quality best practices
• Strong cross-functional collaboration skills to support BI, analytics, and engineering teams

EXPERIENCE: 5+ years of data engineering experience in an AWS-based environment where data powers decision-making across product, marketing, and operations.

YOUR ROLE

Lead scalable data engineering efforts that empower cross-functional teams with reliable, timely, and actionable data, ensuring Launch Potato’s analytics and business intelligence infrastructure fuels strategic growth.

OUTCOMES

• Build and optimize scalable, efficient ETL and data lake processes that proactively catch issues before they impact the business
• Own the ingestion, modeling, and transformation of structured and unstructured data to support reporting and analysis across all business units
• Partner closely with BI and Analytics to deliver clean, query-ready datasets that improve user acquisition, engagement, and revenue growth
• Maintain and enhance database monitoring, anomaly detection, and quality assurance workflows
• Serve as the internal point of contact for reporting infrastructure—delivering ad hoc data analyses and driving consistent data integrity
• Drive adoption and advancement of Looker dashboards by ensuring robust and scalable backend data support
• Contribute to the future of Launch Potato’s data team by mentoring peers and shaping a high-performance, quality-first engineering culture

COMPETENCIES

• Data Engineering Mastery: Demonstrates technical excellence in building data pipelines, troubleshooting distributed systems, and scaling infrastructure using AWS and open-source tools
• Cross-Functional Collaboration: Communicates clearly across technical and non-technical teams, translating business needs into robust data solutions
• Proactive Ownership: Operates with a strong sense of accountability; identifies and solves data issues independently and efficiently
• Quality-Driven Execution: Holds a high bar for data accuracy, auditability, and documentation throughout all systems and workflows
• Strategic Thinking: Anticipates how data infrastructure impacts wider company OKRs and proactively suggests improvements and innovations
• Growth Mindset: Seeks out opportunities to elevate team capabilities, mentor others, and stay ahead of evolving best practices in data engineering

MUST HAVE:

• 5+ years of experience in data engineering within fast-paced, cloud-native environments
• Deep expertise in Python, SQL, Docker, and AWS (S3, Glue, Kinesis, Athena/Presto)
• Experience building and managing scalable ETL pipelines and data lake infrastructure
• Familiarity with distributed systems, Spark, and data quality best practices
• Strong cross-functional collaboration skills to support BI, analytics, and engineering teams

EXPERIENCE: 5+ years of data engineering experience in an AWS-based environment where data powers decision-making across product, marketing, and operations.

YOUR ROLE

Lead scalable data engineering efforts that empower cross-functional teams with reliable, timely, and actionable data, ensuring Launch Potato’s analytics and business intelligence infrastructure fuels strategic growth.

OUTCOMES

• Build and optimize scalable, efficient ETL and data lake processes that proactively catch issues before they impact the business
• Own the ingestion, modeling, and transformation of structured and unstructured data to support reporting and analysis across all business units
• Partner closely with BI and Analytics to deliver clean, query-ready datasets that improve user acquisition, engagement, and revenue growth
• Maintain and enhance database monitoring, anomaly detection, and quality assurance workflows
• Serve as the internal point of contact for reporting infrastructure—delivering ad hoc data analyses and driving consistent data integrity
• Drive adoption and advancement of Looker dashboards by ensuring robust and scalable backend data support
• Contribute to the future of Launch Potato’s data team by mentoring peers and shaping a high-performance, quality-first engineering culture

COMPETENCIES

• Data Engineering Mastery: Demonstrates technical excellence in building data pipelines, troubleshooting distributed systems, and scaling infrastructure using AWS and open-source tools
• Cross-Functional Collaboration: Communicates clearly across technical and non-technical teams, translating business needs into robust data solutions
• Proactive Ownership: Operates with a strong sense of accountability; identifies and solves data issues independently and efficiently
• Quality-Driven Execution: Holds a high bar for data accuracy, auditability, and documentation throughout all systems and workflows
• Strategic Thinking: Anticipates how data infrastructure impacts wider company OKRs and proactively suggests improvements and innovations
• Growth Mindset: Seeks out opportunities to elevate team capabilities, mentor others, and stay ahead of evolving best practices in data engineering

MUST HAVE:

• 5+ years of experience in data engineering within fast-paced, cloud-native environments
• Deep expertise in Python, SQL, Docker, and AWS (S3, Glue, Kinesis, Athena/Presto)
• Experience building and managing scalable ETL pipelines and data lake infrastructure
• Familiarity with distributed systems, Spark, and data quality best practices
• Strong cross-functional collaboration skills to support BI, analytics, and engineering teams

EXPERIENCE: 5+ years of data engineering experience in an AWS-based environment where data powers decision-making across product, marketing, and operations.

YOUR ROLE

Lead scalable data engineering efforts that empower cross-functional teams with reliable, timely, and actionable data, ensuring Launch Potato’s analytics and business intelligence infrastructure fuels strategic growth.

OUTCOMES

• Build and optimize scalable, efficient ETL and data lake processes that proactively catch issues before they impact the business
• Own the ingestion, modeling, and transformation of structured and unstructured data to support reporting and analysis across all business units
• Partner closely with BI and Analytics to deliver clean, query-ready datasets that improve user acquisition, engagement, and revenue growth
• Maintain and enhance database monitoring, anomaly detection, and quality assurance workflows
• Serve as the internal point of contact for reporting infrastructure—delivering ad hoc data analyses and driving consistent data integrity
• Drive adoption and advancement of Looker dashboards by ensuring robust and scalable backend data support
• Contribute to the future of Launch Potato’s data team by mentoring peers and shaping a high-performance, quality-first engineering culture

COMPETENCIES

• Data Engineering Mastery: Demonstrates technical excellence in building data pipelines, troubleshooting distributed systems, and scaling infrastructure using AWS and open-source tools
• Cross-Functional Collaboration: Communicates clearly across technical and non-technical teams, translating business needs into robust data solutions
• Proactive Ownership: Operates with a strong sense of accountability; identifies and solves data issues independently and efficiently
• Quality-Driven Execution: Holds a high bar for data accuracy, auditability, and documentation throughout all systems and workflows
• Strategic Thinking: Anticipates how data infrastructure impacts wider company OKRs and proactively suggests improvements and innovations
• Growth Mindset: Seeks out opportunities to elevate team capabilities, mentor others, and stay ahead of evolving best practices in data engineering

FEQ427R170

Mission

Reporting to a Senior Manager, Field Engineering, the Manager, Field Engineering will help lead a team of Solutions Architects (SAs) for the of Databricks’ Field Engineering team in Latam. You will lead and promote a dynamic team focusing on enterprise software, big data/analytics, data engineering, data science, data warehousing and generative AI. Leading the technical sales team, you will partner with Sales (and other Field Engineering technical  segments)  to increase revenue and help customers become wildly successful. You'll scale and maintain an outstanding Field Engineering team that is efficient in its operations to help accelerate Databricks' growth in the market.

The Impact You Will Have

• You will hire, train, and grow a team of Solutions Architects for a company in high-growth mode.
• Make your customers extremely successful with Databricks and provide outsized value to their businesses.
• You will maintain a robust hiring pipeline at all times.
• Establish relationships across the business to make your customers and team successful.
• Keep your team of SAs ahead of the technical curve. An SA adds value by maintaining advanced knowledge of the technology stack. You will make sure that your team is continuously learning and working to provide our customers with the most comprehensive solutions for their needs

What We Look For

• Proven experience building and leading technical pre(or post)-sales teams - hiring, on-boarding, and enabling pre(or post)-sales professionals
• 10+ years of experience in the data space with a technical product (i.e. data warehousing, big data, machine learning, or more recently with generative AI).
• Trusted advisor to technical executives that guide strategic data infrastructure decisions.
• Lead a team through best practices for technical qualification, technical validations, architecture discussions, and product demonstrations.
• Establish and foster external partnerships with systems integrators (SIs) and independent software vendors (ISVs) that maximize and accelerate client success.
• Strong understanding of consumption-driven business models and the recipes for long term growth and success
• Experience hiring candidates that continually raise the bar, ramping them up to be successful, and promoting into larger roles.
• Create a positive morale for the team and help foster a working relationship between Field Engineering, Sales, and other important internal cross-functional teams.
• Experience working cross-functionally with other teams such as Sales, Product Management, Engineering, and Customer Success.
• Must be technical enough to earn the trust of Engineering talent and leadership at Databricks.
• Demonstrated architectural influence. Able to influence and review complex architectures; guiding your team and customers towards ideal solutions - that scale.

The salary range for this role is $50,000 - $120,000 per year (Gross in USD) 

About Sezzle:

With a mission to financially empower the next generation, Sezzle is revolutionizing the shopping experience beyond payments, blending cutting-edge tech with seamless, interest-free installment plans that make shopping smarter and more accessible. We’re not just transforming payments; we’re redefining how people discover, interact with, and purchase the things they love while driving real impact on merchant sales through increased conversions and higher order values. As we continue to shape the future of fintech and retail, we’re building an innovative, dynamic team passionate about creating more than just a transaction but a truly unique shopping journey. If you’re excited about pushing boundaries in tech and delivering a game-changing experience for consumers and merchants alike, come join us at Sezzle and help create the future of shopping!

About the Role: 

We are seeking a talented and motivated  Sr. AI engineer who is best in class with a high IQ plus a high EQ. This role presents an exciting opportunity to thrive in a dynamic, fast-paced environment within a rapidly growing team, with abundant prospects for career advancement.

You will be responsible for overseeing the design, development, and deployment of machine learning models that power and enhance our financial platform. In this role, you will drive the creation of scalable machine learning solutions for personalized recommendations in the Sezzle marketplace, fraud detection, and credit risk assessment, utilizing a combination of cloud services, open-source tools, and proprietary algorithms.

Your leadership will be key in blending machine learning development and operations (MLOps) to automate and optimize the full lifecycle of our ML models. You will collaborate with a team of engineers and data scientists to build large-scale, high-quality solutions that address diverse challenges in the shopping and fintech space. You’ll ensure our AI-driven features are robust, efficient, and scalable as we continue to grow.

What You'll Do:

• Design, Build, and Maintain Scalable ML Infrastructure: Lead the design and development of scalable machine learning infrastructure on AWS, utilizing services like AWS Sagemaker for efficient model training and deployment.
• Collaborate with Product Teams: Work closely with product teams to develop MVPs for AI-driven features, ensuring quick iterations and market testing to refine solutions effectively.
• Develop Monitoring & Alerting Frameworks: Create and enhance monitoring and alerting systems for machine learning models to ensure high performance, reliability, and minimal downtime.
• Support Cross-Departmental AI Utilization: Enable various departments within the organization to leverage AI/ML models, including cutting-edge Generative AI solutions, for different use cases.
• Provide Production Support: Offer expertise in debugging and resolving issues related to machine learning models in production, participating in on-call rotations for operational troubleshooting and incident resolution.
• Scale ML Architecture: Design and scale machine learning architecture to support rapid user growth, leveraging deep knowledge of AWS and ML best practices to ensure robustness and efficiency.
• Mentor and Elevate Team Skills: Conduct code reviews, mentor team members, and elevate overall team capabilities through knowledge sharing and collaboration.
• Stay Ahead of the Curve: Stay updated with the latest advancements in machine learning technologies and AWS services, driving the adoption of cutting-edge solutions to maintain a competitive edge.

What We Look For:

• Bachelor's degree in Computer Science, Computer Engineering, Machine Learning, Statistics, Physics, or a relevant technical field, or equivalent practical experience.
• At least 6+ years of experience in machine learning engineering, with demonstrated success in deploying scalable ML models in a production environment.

Preferred Qualifications:

• Deep expertise in one or more of the following areas: machine learning, recommendation systems, pattern recognition, data mining, artificial intelligence, or related technical fields.
• Proven track record of developing machine learning models from inception to business impact, demonstrating the ability to solve complex challenges with innovative solutions.
• Proficiency with Python is required, and experience with Golang is a plus.
• Demonstrated technical leadership in guiding teams, owning end-to-end projects, and setting the technical direction to achieve project goals efficiently.
• Experience working with relational databases, data warehouses, and using SQL to explore them.
• Strong familiarity with AWS cloud services, especially in deploying and managing machine learning solutions and scaling them in a cost-effective manner.
• Knowledgeable in Kubernetes, Docker, and CI/CD pipelines for efficient deployment and management of ML models.
• Comfortable with monitoring and observability tools tailored for machine learning models (e.g., Prometheus, Grafana, AWS CloudWatch) and experienced in developing recommender systems or enhancing user experiences through personalized recommendations.
• Solid foundation in data processing and pipeline frameworks (e.g., Apache Spark, Kafka) for handling real-time data streams.

About You:

• You have relentlessly high standards - many people may think your standards are unreasonably high. You are continually raising the bar and driving those around you to deliver great results. You make sure that defects do not get sent down the line and that problems are fixed so they stay fixed.
• You’re not bound by convention - your success—and much of the fun—lies in developing new ways to do things
• You need action - speed matters in business. Many decisions and actions are reversible and do not need extensive study. We value calculated risk-taking.
• You earn trust - you listen attentively, speak candidly, and treat others respectfully.
• You have backbone; disagree, then commit - you can respectfully challenge decisions when you disagree, even when doing so is uncomfortable or exhausting. You have conviction and are tenacious. You do not compromise for the sake of social cohesion. Once a decision is determined, you commit wholly.
• You deliver results - you focus on the key inputs and deliver them with the right quality and in a timely fashion. Despite setbacks, you rise to the occasion and never settle.

What Makes Working at Sezzle Awesome:

At Sezzle, we are more than just brilliant engineers, passionate data enthusiasts, out-of-the-box thinkers, and determined innovators. We believe in surrounding ourselves with only the best and the brightest individuals. Our culture is not defined by a certain set of perks designed to give the illusion of the traditional startup culture, but rather, it is the visible example living in every employee that we hire. 

#Li-remote #full-time

The salary range for this role is negotiable, the range being $6,000-$12,500 per month (Gross in USD), based on location and experience level.  

About Sezzle:

With a mission to financially empower the next generation, Sezzle is revolutionizing the shopping experience beyond payments, blending cutting-edge tech with seamless, interest-free installment plans that make shopping smarter and more accessible. We’re not just transforming payments; we’re redefining how people discover, interact with, and purchase the things they love while driving real impact on merchant sales through increased conversions and higher order values. As we continue to shape the future of fintech and retail, we’re building an innovative, dynamic team passionate about creating more than just a transaction but a truly unique shopping journey. If you’re excited about pushing boundaries in tech and delivering a game-changing experience for consumers and merchants alike, come join us at Sezzle and help create the future of shopping!

Compensation:

For this principal development role, with 12+ years of experience, the compensation range is  $6,000 - $12,500 USD based on location and experience level per month and in gross amount. This range acknowledges the extensive expertise, leadership capabilities, and significant contributions expected at this level, offering a competitive salary to reflect the value of advanced skills and experience

About the Role: 

We are seeking a talented and motivated, best-in-class Principal Engineer for our Data Infrastructure. This role presents an exciting opportunity to thrive in a dynamic, fast-paced environment within a rapidly growing team, with abundant prospects for career advancement.

Sezzle is growing; our data generation and consumption is growing with us at an increasing scale. Data is extremely valuable, and we want to empower the business, the engineers, and the rest of the organization to be able to read, write, and analyze large volumes of it quickly and efficiently.

Sezzle is a heavy consumer of MySQL, Postgres, and Redshift, leveraging AWS tooling with Aurora RDS and DMS. We use DBT-based transformations and similar toolkits to populate a rapidly growing data lake that supports multiple data warehouses. It’s scaled well with us so far, and we’re looking to continue improving it, but we also want to step into new tooling and technologies.

What you’ll do: 

• End to end ownership of our database and data warehousing infrastructure, its KPIs and its SLAs, including MySQL, Postgres, CDC capture, and Redshift.
• Lead optimizations in database and query performance.
• ​​Build and maintain tooling to help manage and upgrade our data infrastructure, continually improving with migrations and optimizations.
• Partner with Development to ensure we ship solid queries against a battle-tested schema to meet the needs of our products and business.

• Help Sezzle evolve our data systems beyond the current scale and stack with whatever tooling is necessary to handle processing high volumes of writes and events while performing complex ETL.
• Evaluate and integrate new technologies, guiding the evolution of Sezzle’s data infrastructure.
• Help data engineers and analysts optimize Redshift and warehouse performance, including query tuning, modeling improvements, and cost management.

What We look for: 

• 12+ years of experience in DBA, SRE, or Data Engineering roles, with a strong track record of scaling production-grade systems.
• Deep expertise with MySQL, Postgres, AWS Redshift or similar products, including performance tuning, table design, and workload management.
• Advanced proficiency in SQL.
• Strong hands-on experience with data replication and ETL/ELT frameworks, especially DBT, AWS DMS, or similar tools.
• Strong understanding of data modeling, distributed systems, and warehouse/lake design patterns.
• Ability to work in a fast-paced, collaborative environment with excellent communication and documentation skills.

Preferred Knowledge and Skills:

• Prior experience in high-growth, data-intensive fintech or similar regulated environments.
• Knowledge of lakehouse architectures and modern stacks such as Snowflake, Databricks, Iceberg, or Delta Lake.
• Some background in designing scalable, fault-tolerant data pipelines using modern orchestration tools (Airflow, Dagster, Prefect, etc.) processing anywhere from 100GB to 1 TB of new data a day
• Familiarity with streaming technologies (Kafka, Kinesis, Flink, Spark Streaming).
• High enthusiasm for using AI to be as productive as possible.

About You: 

• You have relentlessly high standards - many people may think your standards are unreasonably high. You are continually raising the bar and driving those around you to deliver great results. You make sure that defects do not get sent down the line and that problems are fixed so they stay fixed.
• You’re not bound by convention - your success—and much of the fun—lies in developing new ways to do things
• You need action - speed matters in business. Many decisions and actions are reversible and do not need extensive study. We value calculated risk-taking.
• You earn trust - you listen attentively, speak candidly, and treat others respectfully.
• You have backbone; disagree, then commit - you can respectfully challenge decisions when you disagree, even when doing so is uncomfortable or exhausting. You have conviction and are tenacious. You do not compromise for the sake of social cohesion. Once a decision is determined, you commit wholly.
• You deliver results - you focus on the key inputs and deliver them with the right quality and in a timely fashion. Despite setbacks, you rise to the occasion and never settle.

Sezzle’s Technology Stack:

• Languages: Golang, Typescript, Python
• Frontend: Typescript - React and React Native
• Backend: Golang
• Database: MySQL, Postgres, Elasticsearch
• DevOps & Cloud: AWS, Kubernetes
• Version Control: Git
• CI/CD: Gitlab
• Testing: Developer and AI-driven, focus on automated end-to-end, integration, and unit tests
• Open Source: Sezzle is focused on using open source, and we build what we can before buying!

What Makes Working at Sezzle Awesome? 

At Sezzle, we are more than just brilliant engineers, passionate data enthusiasts, out-of-the-box thinkers, and determined innovators; we are skilled musicians, yogis, cyclists, chefs, golfers, dog-lovers, and rock-climbers. We believe in surrounding ourselves with not only the best and the brightest individuals, but those that are unique and purpose-driven in all that they do. Our culture is not defined by a certain set of perks designed to give the illusion of the traditional startup culture, but rather, it is the visible example living in every employee that we hire.

#Li-remote #full-time

The salary range for this role is $50,000 - $120,000 per year (Gross in USD) 

About Sezzle:

With a mission to financially empower the next generation, Sezzle is revolutionizing the shopping experience beyond payments, blending cutting-edge tech with seamless, interest-free installment plans that make shopping smarter and more accessible. We’re not just transforming payments; we’re redefining how people discover, interact with, and purchase the things they love while driving real impact on merchant sales through increased conversions and higher order values. As we continue to shape the future of fintech and retail, we’re building an innovative, dynamic team passionate about creating more than just a transaction but a truly unique shopping journey. If you’re excited about pushing boundaries in tech and delivering a game-changing experience for consumers and merchants alike, come join us at Sezzle and help create the future of shopping!

About the Role: 

We are seeking a talented and motivated Sr. AI engineer who is best in class with a high IQ plus a high EQ. This role presents an exciting opportunity to thrive in a dynamic, fast-paced environment within a rapidly growing team, with abundant prospects for career advancement.

You will be responsible for overseeing the design, development, and deployment of machine learning models that power and enhance our financial platform. In this role, you will drive the creation of scalable machine learning solutions for personalized recommendations in the Sezzle marketplace, fraud detection, and credit risk assessment, utilizing a combination of cloud services, open-source tools, and proprietary algorithms.

Your leadership will be key in blending machine learning development and operations (MLOps) to automate and optimize the full lifecycle of our ML models. You will collaborate with a team of engineers and data scientists to build large-scale, high-quality solutions that address diverse challenges in the shopping and fintech space. You’ll ensure our AI-driven features are robust, efficient, and scalable as we continue to grow.

What You'll Do:

• Design, Build, and Maintain Scalable ML Infrastructure: Lead the design and development of scalable machine learning infrastructure on AWS, utilizing services like AWS Sagemaker for efficient model training and deployment.
• Collaborate with Product Teams: Work closely with product teams to develop MVPs for AI-driven features, ensuring quick iterations and market testing to refine solutions effectively.
• Develop Monitoring & Alerting Frameworks: Create and enhance monitoring and alerting systems for machine learning models to ensure high performance, reliability, and minimal downtime.
• Support Marketing Team’s AI Utilization with an eye on Cross-Departmental impact: Enable various departments within the organization to leverage AI/ML models, including cutting-edge Generative AI solutions, for different use cases.
• Provide Production Support: Offer expertise in debugging and resolving issues related to machine learning models in production, participating in on-call rotations for operational troubleshooting and incident resolution.
• Scale ML Architecture: Design and scale machine learning architecture to support rapid user growth, leveraging deep knowledge of AWS and ML best practices to ensure robustness and efficiency.
• Mentor and Elevate Team Skills: Conduct code reviews, mentor team members, and elevate overall team capabilities through knowledge sharing and collaboration.
• Stay Ahead of the Curve: Stay updated with the latest advancements in machine learning technologies and AWS services, driving the adoption of cutting-edge solutions to maintain a competitive edge.

What We Look For:

• Bachelor's degree in Computer Science, Computer Engineering, Machine Learning, Statistics, Physics, or a relevant technical field, or equivalent practical experience.
• At least 6+ years of experience in machine learning engineering, with demonstrated success in deploying scalable ML models in a production environment.

Preferred Qualifications:

• Deep expertise in one or more of the following areas: machine learning, recommendation systems, pattern recognition, data mining, artificial intelligence, or related technical fields.
• Proven track record of developing machine learning models from inception to business impact, demonstrating the ability to solve complex challenges with innovative solutions.
• Proficiency with Python is required, and experience with Golang is a plus.
• Demonstrated technical leadership in guiding teams, owning end-to-end projects, and setting the technical direction to achieve project goals efficiently.
• Experience working with relational databases, data warehouses, and using SQL to explore them.
• Strong familiarity with AWS cloud services, especially in deploying and managing machine learning solutions and scaling them in a cost-effective manner.
• Knowledgeable in Kubernetes, Docker, and CI/CD pipelines for efficient deployment and management of ML models.
• Comfortable with monitoring and observability tools tailored for machine learning models (e.g., Prometheus, Grafana, AWS CloudWatch) and experienced in developing recommender systems or enhancing user experiences through personalized recommendations.
• Solid foundation in data processing and pipeline frameworks (e.g., Apache Spark, Kafka) for handling real-time data streams.

About You:

• You have relentlessly high standards - many people may think your standards are unreasonably high. You are continually raising the bar and driving those around you to deliver great results. You make sure that defects do not get sent down the line and that problems are fixed so they stay fixed.
• You’re not bound by convention - your success—and much of the fun—lies in developing new ways to do things
• You need action - speed matters in business. Many decisions and actions are reversible and do not need extensive study. We value calculated risk-taking.
• You earn trust - you listen attentively, speak candidly, and treat others respectfully.
• You have backbone; disagree, then commit - you can respectfully challenge decisions when you disagree, even when doing so is uncomfortable or exhausting. You have conviction and are tenacious. You do not compromise for the sake of social cohesion. Once a decision is determined, you commit wholly.
• You deliver results - you focus on the key inputs and deliver them with the right quality and in a timely fashion. Despite setbacks, you rise to the occasion and never settle.

What Makes Working at Sezzle Awesome:

At Sezzle, we are more than just brilliant engineers, passionate data enthusiasts, out-of-the-box thinkers, and determined innovators. We believe in surrounding ourselves with only the best and the brightest individuals. Our culture is not defined by a certain set of perks designed to give the illusion of the traditional startup culture, but rather, it is the visible example living in every employee that we hire. 

#Li-remote #full-time

Our ELT (Extract, Load, Transform) application simplifies data workflows, enabling organizations to extract insights faster, automate repetitive tasks, and unlock the true potential of their data.

We are looking for a Lead Software Engineer with deep experience designing and scaling large-scale, data-intensive systems. This role requires hands-on expertise working with massive datasets, distributed data pipelines, and high-throughput backend architectures. You will play a key role in driving our backend services, data platforms, and cloud-native systems forward.

What You’ll Do

• Design, build, and scale new features for REST APIs and large-scale data processing pipelines that handle high-volume datasets across distributed systems.
• Architect and optimize backend services for high throughput and low-latency performance.
• Develop data-intensive and event-driven applications using Python, Typescript, Spark, and AWS-native services.
• Work with Spark, EMR, Glue, Kafka, or similar frameworks to process and transform very large datasets.
• Improve system performance, reliability, and scalability across microservices and cloud infrastructure.
• Partner with senior engineers, architects, DevOps, and QA throughout the full development lifecycle.
• Mentor developers, guide code reviews, and raise engineering quality standards.
• Automate deployments and CI/CD using Terraform, Serverless Framework, and Kubernetes-based workflows.

What You Bring

Technical Expertise

• 7+ years of backend or full-stack engineering experience with a strong backend focus.
• 7+ years of hands-on Python experience (APIs, automation, large-scale data pipelines).
• 3+ years working with Typescript / Node.js.
• Advanced experience with AWS (EC2, EKS, Lambda, S3, DynamoDB, RDS, Step Functions, etc.).
• Strong practical experience deploying and optimizing production workloads on Kubernetes.
• Proven experience working with large datasets, distributed computing, and batch or stream processing using Spark, Dask, EMR, Glue, Kafka, etc.
• Solid understanding of system design, distributed systems, scalability patterns, and cloud architecture.

Collaboration & Communication

• Strong business-level English proficiency to communicate effectively with cross-functional teams across regions.
• Ability to collaborate, document solutions clearly, and participate in technical discussions with stakeholders.

🗒️ Note: 

• Candidates selected for this position will be hired directly by Varicent.
• This role requires employees to work within Eastern Standard Time (EST) business hours. While we are open to candidates from outside the EST time zone, please be prepared to adjust your working hours to align with this time zone. Flexibility will be essential to ensure seamless collaboration with the team and stakeholders. 
• This position is fully remote, offering you the flexibility to work from anywhere. We embrace a results-driven work culture, focusing on performance and collaboration over location. As part of our team, you’ll have the opportunity to build a work-life balance that suits you, while staying connected with a diverse, global team through virtual tools and regular online communication. Whether you're working from home, a co-working space, or another location of your choice, we’re committed to supporting you with the resources and autonomy needed to succeed in a remote environment. 

🍎 Benefits 

• Market Leading Compensation Package.
• Wellness Programs to Support Health and Wellbeing.
• Working with the latest tools and technologies in a fast-paced environment.
• Remote Work Flexibility.
• Comprehensive Employee Insurance Coverage: Medical, Dental, Vision, Life Insurance.
• Annual Time Off: Time off is provided in accordance with applicable legislative requirements.
• Global Connected Culture: Hubs in Romania, UK, US, Canada.
• Dynamic Work Culture: Thrive in our innovative and multicultural environment.
• Grow with Us: Continuous development opportunities.

Our ELT (Extract, Load, Transform) application simplifies data workflows, enabling organizations to extract insights faster, automate repetitive tasks, and unlock the true potential of their data.

We are looking for a Senior Software Engineer with deep experience designing and scaling large-scale, data-intensive systems. This role requires hands-on expertise working with massive datasets, distributed data pipelines, and high-throughput backend architectures. You will play a key role in driving our backend services, data platforms, and cloud-native systems forward.

What You’ll Do

• Design, build, and scale new features for REST APIs and large-scale data processing pipelines that handle high-volume datasets across distributed systems.
• Architect and optimize backend services for high throughput and low-latency performance.
• Develop data-intensive and event-driven applications using Python, Typescript, Spark, and AWS-native services.
• Work with Spark, EMR, Glue, Kafka, or similar frameworks to process and transform very large datasets.
• Improve system performance, reliability, and scalability across microservices and cloud infrastructure.
• Partner with senior engineers, architects, DevOps, and QA throughout the full development lifecycle.
• Mentor developers, guide code reviews, and raise engineering quality standards.
• Automate deployments and CI/CD using Terraform, Serverless Framework, and Kubernetes-based workflows.

What You Bring

Technical Expertise

• 7+ years of backend or full-stack engineering experience with a strong backend focus.
• 7+ years of hands-on Python experience (APIs, automation, large-scale data pipelines).
• 3+ years working with Typescript / Node.js.
• Advanced experience with AWS (EC2, EKS, Lambda, S3, DynamoDB, RDS, Step Functions, etc.).
• Strong practical experience deploying and optimizing production workloads on Kubernetes.
• Proven experience working with large datasets, distributed computing, and batch or stream processing using Spark, Dask, EMR, Glue, Kafka, etc.
• Solid understanding of system design, distributed systems, scalability patterns, and cloud architecture.

Collaboration & Communication

• Strong business-level English proficiency to communicate effectively with cross-functional teams across regions.
• Ability to collaborate, document solutions clearly, and participate in technical discussions with stakeholders.

🗒️ Note: 

• Candidates selected for this position will be hired directly by Varicent.
• This role requires employees to work within Eastern Standard Time (EST) business hours. While we are open to candidates from outside the EST time zone, please be prepared to adjust your working hours to align with this time zone. Flexibility will be essential to ensure seamless collaboration with the team and stakeholders. 
• This position is fully remote, offering you the flexibility to work from anywhere. We embrace a results-driven work culture, focusing on performance and collaboration over location. As part of our team, you’ll have the opportunity to build a work-life balance that suits you, while staying connected with a diverse, global team through virtual tools and regular online communication. Whether you're working from home, a co-working space, or another location of your choice, we’re committed to supporting you with the resources and autonomy needed to succeed in a remote environment. 

🍎 Benefits 

• Market Leading Compensation Package.
• Wellness Programs to Support Health and Wellbeing.
• Working with the latest tools and technologies in a fast-paced environment.
• Remote Work Flexibility.
• Comprehensive Employee Insurance Coverage: Medical, Dental, Vision, Life Insurance.
• Annual Time Off: Time off is provided in accordance with applicable legislative requirements.
• Global Connected Culture: Hubs in Romania, UK, US, Canada.
• Dynamic Work Culture: Thrive in our innovative and multicultural environment.
• Grow with Us: Continuous development opportunities.

Our ELT (Extract, Load, Transform) application simplifies data workflows, enabling organizations to extract insights faster, automate repetitive tasks, and unlock the true potential of their data.

We are looking for a Senior Software Engineer with deep experience designing and scaling large-scale, data-intensive systems. This role requires hands-on expertise working with massive datasets, distributed data pipelines, and high-throughput backend architectures. You will play a key role in driving our backend services, data platforms, and cloud-native systems forward.

What You’ll Do

• Design, build, and scale new features for REST APIs and large-scale data processing pipelines that handle high-volume datasets across distributed systems.
• Architect and optimize backend services for high throughput and low-latency performance.
• Develop data-intensive and event-driven applications using Python, Typescript, Spark, and AWS-native services.
• Work with Spark, EMR, Glue, Kafka, or similar frameworks to process and transform very large datasets.
• Improve system performance, reliability, and scalability across microservices and cloud infrastructure.
• Partner with senior engineers, architects, DevOps, and QA throughout the full development lifecycle.
• Mentor developers, guide code reviews, and raise engineering quality standards.
• Automate deployments and CI/CD using Terraform, Serverless Framework, and Kubernetes-based workflows.

What You Bring

Technical Expertise

• 7+ years of backend or full-stack engineering experience with a strong backend focus.
• 7+ years of hands-on Python experience (APIs, automation, large-scale data pipelines).
• 3+ years working with Typescript / Node.js.
• Advanced experience with AWS (EC2, EKS, Lambda, S3, DynamoDB, RDS, Step Functions, etc.).
• Strong practical experience deploying and optimizing production workloads on Kubernetes.
• Proven experience working with large datasets, distributed computing, and batch or stream processing using Spark, Dask, EMR, Glue, Kafka, etc.
• Solid understanding of system design, distributed systems, scalability patterns, and cloud architecture.

Collaboration & Communication

• Strong business-level English proficiency to communicate effectively with cross-functional teams across regions.
• Ability to collaborate, document solutions clearly, and participate in technical discussions with stakeholders.

🗒️ Note: 

• Candidates selected for this position will be hired directly by Varicent.
• This role requires employees to work within Eastern Standard Time (EST) business hours. While we are open to candidates from outside the EST time zone, please be prepared to adjust your working hours to align with this time zone. Flexibility will be essential to ensure seamless collaboration with the team and stakeholders. 
• This position is fully remote, offering you the flexibility to work from anywhere. We embrace a results-driven work culture, focusing on performance and collaboration over location. As part of our team, you’ll have the opportunity to build a work-life balance that suits you, while staying connected with a diverse, global team through virtual tools and regular online communication. Whether you're working from home, a co-working space, or another location of your choice, we’re committed to supporting you with the resources and autonomy needed to succeed in a remote environment. 

🍎 Benefits 

• Market Leading Compensation Package.
• Wellness Programs to Support Health and Wellbeing.
• Working with the latest tools and technologies in a fast-paced environment.
• Remote Work Flexibility.
• Comprehensive Employee Insurance Coverage: Medical, Dental, Vision, Life Insurance.
• Annual Time Off: Time off is provided in accordance with applicable legislative requirements.
• Global Connected Culture: Hubs in Romania, UK, US, Canada.
• Dynamic Work Culture: Thrive in our innovative and multicultural environment.
• Grow with Us: Continuous development opportunities.

Our ELT (Extract, Load, Transform) application simplifies data workflows, enabling organizations to extract insights faster, automate repetitive tasks, and unlock the true potential of their data.

We are looking for a Senior Software Engineer with deep experience designing and scaling large-scale, data-intensive systems. This role requires hands-on expertise working with massive datasets, distributed data pipelines, and high-throughput backend architectures. You will play a key role in driving our backend services, data platforms, and cloud-native systems forward.

What You’ll Do

• Design, build, and scale new features for REST APIs and large-scale data processing pipelines that handle high-volume datasets across distributed systems.
• Architect and optimize backend services for high throughput and low-latency performance.
• Develop data-intensive and event-driven applications using Python, Typescript, Spark, and AWS-native services.
• Work with Spark, EMR, Glue, Kafka, or similar frameworks to process and transform very large datasets.
• Improve system performance, reliability, and scalability across microservices and cloud infrastructure.
• Partner with senior engineers, architects, DevOps, and QA throughout the full development lifecycle.
• Mentor developers, guide code reviews, and raise engineering quality standards.
• Automate deployments and CI/CD using Terraform, Serverless Framework, and Kubernetes-based workflows.

What You Bring

Technical Expertise

• 7+ years of backend or full-stack engineering experience with a strong backend focus.
• 7+ years of hands-on Python experience (APIs, automation, large-scale data pipelines).
• 3+ years working with Typescript / Node.js.
• Advanced experience with AWS (EC2, EKS, Lambda, S3, DynamoDB, RDS, Step Functions, etc.).
• Strong practical experience deploying and optimizing production workloads on Kubernetes.
• Proven experience working with large datasets, distributed computing, and batch or stream processing using Spark, Dask, EMR, Glue, Kafka, etc.
• Solid understanding of system design, distributed systems, scalability patterns, and cloud architecture.

Collaboration & Communication

• Strong business-level English proficiency to communicate effectively with cross-functional teams across regions.
• Ability to collaborate, document solutions clearly, and participate in technical discussions with stakeholders.

🗒️ Note: 

• Candidates selected for this position will be hired directly by Varicent.
• This role requires employees to work within Eastern Standard Time (EST) business hours. While we are open to candidates from outside the EST time zone, please be prepared to adjust your working hours to align with this time zone. Flexibility will be essential to ensure seamless collaboration with the team and stakeholders. 
• This position is fully remote, offering you the flexibility to work from anywhere. We embrace a results-driven work culture, focusing on performance and collaboration over location. As part of our team, you’ll have the opportunity to build a work-life balance that suits you, while staying connected with a diverse, global team through virtual tools and regular online communication. Whether you're working from home, a co-working space, or another location of your choice, we’re committed to supporting you with the resources and autonomy needed to succeed in a remote environment. 

🍎 Benefits 

• Market Leading Compensation Package.
• Wellness Programs to Support Health and Wellbeing.
• Working with the latest tools and technologies in a fast-paced environment.
• Remote Work Flexibility.
• Comprehensive Employee Insurance Coverage: Medical, Dental, Vision, Life Insurance.
• Annual Time Off: Time off is provided in accordance with applicable legislative requirements.
• Global Connected Culture: Hubs in Romania, UK, US, Canada.
• Dynamic Work Culture: Thrive in our innovative and multicultural environment.
• Grow with Us: Continuous development opportunities.

Our ELT (Extract, Load, Transform) application simplifies data workflows, enabling organizations to extract insights faster, automate repetitive tasks, and unlock the true potential of their data.

We are looking for a Senior Software Engineer with deep experience designing and scaling large-scale, data-intensive systems. This role requires hands-on expertise working with massive datasets, distributed data pipelines, and high-throughput backend architectures. You will play a key role in driving our backend services, data platforms, and cloud-native systems forward.

What You’ll Do

• Design, build, and scale new features for REST APIs and large-scale data processing pipelines that handle high-volume datasets across distributed systems.
• Architect and optimize backend services for high throughput and low-latency performance.
• Develop data-intensive and event-driven applications using Python, Typescript, Spark, and AWS-native services.
• Work with Spark, EMR, Glue, Kafka, or similar frameworks to process and transform very large datasets.
• Improve system performance, reliability, and scalability across microservices and cloud infrastructure.
• Partner with senior engineers, architects, DevOps, and QA throughout the full development lifecycle.
• Mentor developers, guide code reviews, and raise engineering quality standards.
• Automate deployments and CI/CD using Terraform, Serverless Framework, and Kubernetes-based workflows.

What You Bring

Technical Expertise

• 7+ years of backend or full-stack engineering experience with a strong backend focus.
• 7+ years of hands-on Python experience (APIs, automation, large-scale data pipelines).
• 3+ years working with Typescript / Node.js.
• Advanced experience with AWS (EC2, EKS, Lambda, S3, DynamoDB, RDS, Step Functions, etc.).
• Strong practical experience deploying and optimizing production workloads on Kubernetes.
• Proven experience working with large datasets, distributed computing, and batch or stream processing using Spark, Dask, EMR, Glue, Kafka, etc.
• Solid understanding of system design, distributed systems, scalability patterns, and cloud architecture.

Collaboration & Communication

• Strong business-level English proficiency to communicate effectively with cross-functional teams across regions.
• Ability to collaborate, document solutions clearly, and participate in technical discussions with stakeholders.

🗒️ Note: 

• Candidates selected for this position will be hired directly by Varicent.
• This role requires employees to work within Eastern Standard Time (EST) business hours. While we are open to candidates from outside the EST time zone, please be prepared to adjust your working hours to align with this time zone. Flexibility will be essential to ensure seamless collaboration with the team and stakeholders. 
• This position is fully remote, offering you the flexibility to work from anywhere. We embrace a results-driven work culture, focusing on performance and collaboration over location. As part of our team, you’ll have the opportunity to build a work-life balance that suits you, while staying connected with a diverse, global team through virtual tools and regular online communication. Whether you're working from home, a co-working space, or another location of your choice, we’re committed to supporting you with the resources and autonomy needed to succeed in a remote environment. 

🍎 Benefits 

• Market Leading Compensation Package.
• Wellness Programs to Support Health and Wellbeing.
• Working with the latest tools and technologies in a fast-paced environment.
• Remote Work Flexibility.
• Comprehensive Employee Insurance Coverage: Medical, Dental, Vision, Life Insurance.
• Annual Time Off: Time off is provided in accordance with applicable legislative requirements.
• Global Connected Culture: Hubs in Romania, UK, US, Canada.
• Dynamic Work Culture: Thrive in our innovative and multicultural environment.
• Grow with Us: Continuous development opportunities.

Our ELT (Extract, Load, Transform) application simplifies data workflows, enabling organizations to extract insights faster, automate repetitive tasks, and unlock the true potential of their data.

We are looking for a Staff Software Engineer with deep experience designing and scaling large-scale, data-intensive systems. This role requires hands-on expertise working with massive datasets, distributed data pipelines, and high-throughput backend architectures. You will play a key role in driving our backend services, data platforms, and cloud-native systems forward.

What You’ll Do

• Design, build, and scale new features for REST APIs and large-scale data processing pipelines that handle high-volume datasets across distributed systems.
• Architect and optimize backend services for high throughput and low-latency performance.
• Develop data-intensive and event-driven applications using Python, Typescript, Spark, and AWS-native services.
• Work with Spark, EMR, Glue, Kafka, or similar frameworks to process and transform very large datasets.
• Improve system performance, reliability, and scalability across microservices and cloud infrastructure.
• Partner with senior engineers, architects, DevOps, and QA throughout the full development lifecycle.
• Mentor developers, guide code reviews, and raise engineering quality standards.
• Automate deployments and CI/CD using Terraform, Serverless Framework, and Kubernetes-based workflows.

What You Bring

Technical Expertise

• 7+ years of backend or full-stack engineering experience with a strong backend focus.
• 7+ years of hands-on Python experience (APIs, automation, large-scale data pipelines).
• 3+ years working with Typescript / Node.js.
• Advanced experience with AWS (EC2, EKS, Lambda, S3, DynamoDB, RDS, Step Functions, etc.).
• Strong practical experience deploying and optimizing production workloads on Kubernetes.
• Proven experience working with large datasets, distributed computing, and batch or stream processing using Spark, Dask, EMR, Glue, Kafka, etc.
• Solid understanding of system design, distributed systems, scalability patterns, and cloud architecture.

Collaboration & Communication

• Strong business-level English proficiency to communicate effectively with cross-functional teams across regions.
• Ability to collaborate, document solutions clearly, and participate in technical discussions with stakeholders.

🗒️ Note: 

• Candidates selected for this position will be hired directly by Varicent.
• This role requires employees to work within Eastern Standard Time (EST) business hours. While we are open to candidates from outside the EST time zone, please be prepared to adjust your working hours to align with this time zone. Flexibility will be essential to ensure seamless collaboration with the team and stakeholders. 
• This position is fully remote, offering you the flexibility to work from anywhere. We embrace a results-driven work culture, focusing on performance and collaboration over location. As part of our team, you’ll have the opportunity to build a work-life balance that suits you, while staying connected with a diverse, global team through virtual tools and regular online communication. Whether you're working from home, a co-working space, or another location of your choice, we’re committed to supporting you with the resources and autonomy needed to succeed in a remote environment. 

🍎 Benefits 

• Market Leading Compensation Package.
• Wellness Programs to Support Health and Wellbeing.
• Working with the latest tools and technologies in a fast-paced environment.
• Remote Work Flexibility.
• Comprehensive Employee Insurance Coverage: Medical, Dental, Vision, Life Insurance.
• Annual Time Off: Time off is provided in accordance with applicable legislative requirements.
• Global Connected Culture: Hubs in Romania, UK, US, Canada.
• Dynamic Work Culture: Thrive in our innovative and multicultural environment.
• Grow with Us: Continuous development opportunities.

Our ELT (Extract, Load, Transform) application simplifies data workflows, enabling organizations to extract insights faster, automate repetitive tasks, and unlock the true potential of their data.

We are looking for a Staff Software Engineer with deep experience designing and scaling large-scale, data-intensive systems. This role requires hands-on expertise working with massive datasets, distributed data pipelines, and high-throughput backend architectures. You will play a key role in driving our backend services, data platforms, and cloud-native systems forward.

What You’ll Do

• Design, build, and scale new features for REST APIs and large-scale data processing pipelines that handle high-volume datasets across distributed systems.
• Architect and optimize backend services for high throughput and low-latency performance.
• Develop data-intensive and event-driven applications using Python, Typescript, Spark, and AWS-native services.
• Work with Spark, EMR, Glue, Kafka, or similar frameworks to process and transform very large datasets.
• Improve system performance, reliability, and scalability across microservices and cloud infrastructure.
• Partner with senior engineers, architects, DevOps, and QA throughout the full development lifecycle.
• Mentor developers, guide code reviews, and raise engineering quality standards.
• Automate deployments and CI/CD using Terraform, Serverless Framework, and Kubernetes-based workflows.

What You Bring

Technical Expertise

• 7+ years of backend or full-stack engineering experience with a strong backend focus.
• 7+ years of hands-on Python experience (APIs, automation, large-scale data pipelines).
• 3+ years working with Typescript / Node.js.
• Advanced experience with AWS (EC2, EKS, Lambda, S3, DynamoDB, RDS, Step Functions, etc.).
• Strong practical experience deploying and optimizing production workloads on Kubernetes.
• Proven experience working with large datasets, distributed computing, and batch or stream processing using Spark, Dask, EMR, Glue, Kafka, etc.
• Solid understanding of system design, distributed systems, scalability patterns, and cloud architecture.

Collaboration & Communication

• Strong business-level English proficiency to communicate effectively with cross-functional teams across regions.
• Ability to collaborate, document solutions clearly, and participate in technical discussions with stakeholders.

🗒️ Note: 

• Candidates selected for this position will be hired directly by Varicent.
• This role requires employees to work within Eastern Standard Time (EST) business hours. While we are open to candidates from outside the EST time zone, please be prepared to adjust your working hours to align with this time zone. Flexibility will be essential to ensure seamless collaboration with the team and stakeholders. 
• This position is fully remote, offering you the flexibility to work from anywhere. We embrace a results-driven work culture, focusing on performance and collaboration over location. As part of our team, you’ll have the opportunity to build a work-life balance that suits you, while staying connected with a diverse, global team through virtual tools and regular online communication. Whether you're working from home, a co-working space, or another location of your choice, we’re committed to supporting you with the resources and autonomy needed to succeed in a remote environment. 

🍎 Benefits 

• Market Leading Compensation Package.
• Wellness Programs to Support Health and Wellbeing.
• Working with the latest tools and technologies in a fast-paced environment.
• Remote Work Flexibility.
• Comprehensive Employee Insurance Coverage: Medical, Dental, Vision, Life Insurance.
• Annual Time Off: Time off is provided in accordance with applicable legislative requirements.
• Global Connected Culture: Hubs in Romania, UK, US, Canada.
• Dynamic Work Culture: Thrive in our innovative and multicultural environment.
• Grow with Us: Continuous development opportunities.

Type: Contract, per-project.
Location: Remote — within LATAM with ET ±1 hour
Availability: Contractor (40 hours per week)

Job Title: Data / Platform Engineer (AWS & Data Pipelines)

We are looking for a highly motivated Data / Platform Engineer to join our team and help design, build and operate scalable data pipelines and cloud-based solutions.

In this role, you will work closely with engineering and product teams to build both streaming and batch data pipelines, contribute to system design, and help drive automation and monitoring across our data platform.

Key Responsibilities

• Design, build, maintain and primarily operate scalable streaming and batch data pipelines, with a strong focus on maintenance, monitoring, troubleshooting and continuous improvement of existing pipelines.

• Work with AWS services, including Redshift, EMR and ECS, to support data processing and analytics workloads.

• Develop and maintain data workflows using Python and SQL.

• Orchestrate and monitor pipelines using Apache Airflow.

• Build and deploy containerized applications using Docker and Kubernetes.

• Break down high-level system designs into well-defined, deliverable tasks with realistic estimates.

• Collaborate with cross-functional teams in a fast-paced and distributed environment across the US and Europe.

• Drive automation, observability and monitoring to improve reliability, performance and operational efficiency.

• Support knowledge transfer and ownership handover as part of the planned transition to the consuming team.

Required Qualifications

• Strong professional experience with Python and SQL.

• Hands-on experience with AWS, specifically Redshift, EMR and ECS. AWS experience is mandatory (other cloud providers are not considered equivalent for this role).

• Proven experience building and operating both streaming and batch data pipelines.

• Professional experience with Apache Airflow, Docker and Kubernetes.

• Ability to translate high-level system designs into actionable technical tasks and realistic estimates.

• Comfortable working in dynamic and fast-paced environments and in distributed teams.

• Strong interest in automation and monitoring.

• Strong hands-on experience with Apache Spark.

• Senior-level profile with strong autonomy, communication skills and ability to work effectively in distributed teams.

• Proven ability to transfer knowledge and support ownership handovers.

• Fluent or professional working proficiency in English (both written and spoken).

Nice to Have

• Previous experience in the telecom industry.

• Experience with machine learning systems and/or event-driven architectures.

• Experience with Apache Iceberg.
  
  (*) SOUTHWORKS only hires individuals from countries that are not blocked or sanctioned by the United States, including those identified on the United States Office of Foreign Asset Control (OFAC).

Type: Contract, per-project.
Location: Remote - within LATAM time zones (GMT-3 to GMT-5) - Remote with meetings across U.S. time zones
Availability: Contractor (40 hours per week)

Windows Application Developer - Partner Engineer
We’re looking for a Windows Application Developer - Partner Engineer to join our Windows Ecosystem Enablement team.
This role is focused on helping strategic ISV partners bring their desktop applications into the Windows ecosystem and the Microsoft Store. You will work directly with senior engineers, solve complex packaging and platform issues, build reference implementations, and navigate Microsoft’s internal teams to unblock partner success.
This is not a traditional Windows developer role. We are looking for someone with deep understanding of the Windows ecosystem—someone who understands how software is packaged, distributed, installed, and integrated at the OS level.

Core Responsibilities
Partner Technical Support & Onboarding

• Support ISV partners with packaging, publishing, and onboarding applications into the Microsoft Store

• Resolve technical blockers related to installers, Store dependencies, Windows Update, drivers, policies, and OS-level integrations

• Help partners adopt the right architecture across Win32, .NET, UWP, WebView2, PWA, MSIX, and unpackaged app models

Prototyping & Technical Problem Solving

• Build small tools, sample apps, sandbox environments, and reference implementations to reproduce and solve partner issues

• Create proof-of-concepts without touching client codebases

• Deliver targeted fixes across packaging workflows, SDK usage, and publishing processes

Internal Microsoft Collaboration

• Work across Microsoft teams including Windows Store, WinGet, Copilot, and platform engineering groups

• Identify the right internal stakeholders, escalate technical blockers, and drive solutions across siloed teams

• Support high-priority partner escalations in fast-moving, cross-functional environments

Documentation & Best Practices

• Create technical guides, internal playbooks, and reusable reference implementations based on partner learnings

• Document packaging best practices and onboarding standards for Microsoft teams and ISV partners

• Help establish scalable technical guidance for future partner onboarding

Partner Outreach

• Support outreach efforts to software vendors not yet publishing in the Microsoft Store

• Help qualify leads, follow up with ISVs, and support partner adoption initiatives

Required Experience
Strong Windows Ecosystem Background

• 5+ years of experience working with Windows applications and desktop software distribution

• Strong understanding of installers, drivers, OS-level APIs, software packaging, and Windows platform integrations

• Experience across Win32, .NET, UWP, WebView2, PWAs, or similar desktop architectures

Commercial Software Distribution Experience

• Background working at companies that ship and distribute commercial software products

• Exposure to packaging, deployment, signing, Store submission, and operating system integration

• Experience only building internal business systems is not enough for this role

Prototyping & Troubleshooting Mindset

• Ability to independently reproduce issues, create sandbox environments, and build reference implementations

• Strong problem-solving skills across low-level platform issues and technical ambiguity

Strong Communication & Ownership

• Comfortable working directly with clients and senior engineers

• Able to explain technical tradeoffs clearly and drive solutions proactively

• Strong ownership mindset with a bias toward action

Nice to Have

• Experience with MSIX, unpackaged apps, Xbox-to-Windows migration, PWA packaging, and Windows Store publishing

• Familiarity with installer technologies such as WiX

• Experience with GitHub Actions, SDK fixes, and CI publishing workflows

• Data pipeline literacy (Spark, Fabric, large-scale systems)

• Experience using AI tools like Copilot for prototyping and workflow acceleration

• Previous Microsoft experience is a strong plus
  
  (*) SOUTHWORKS only hires individuals from countries that are not blocked or sanctioned by the United States, including those identified on the United States Office of Foreign Asset Control (OFAC).

The Mission

This is a senior role for someone who leads from both directions at once — deeply technical on customer engagements, and fully accountable for the growth and performance of a team of ML engineers and architects. You will report to the Director of AI/ML.

You own hiring, development, and team health alongside leading complex customer engagements, shaping architecture, and driving pre-sales. Both parts of this job are real and ongoing. The right candidate will find energy in that combination, not tension.

Your Assignment

Leading Your Team

• Hire and build: Set the technical bar for ML roles on your team, lead or oversee technical assessments, and make hiring decisions you can stand behind. Build a team that raises the practice's overall standard.
• Develop people: Run regular structured 1:1s, provide candid feedback at meaningful milestones, and actively invest in each person's growth — whether they are early in their career or highly experienced.
• Manage performance: Recognize strong contributors and address performance gaps directly and early. Partner with HRBPs and the Director of AI/ML when situations require a structured path, and advocate for your team when they deserve it.
• Stay close to staffing: Understand how your team is utilized across engagements, keep the staffing team informed of each person's skills evolution and preferences, and ensure people are placed in work that stretches them appropriately.

Strategic Advisory

• Lead ML assessments: Evaluate customer environments end-to-end — infrastructure, data pipelines, model lifecycle, and organizational readiness — and produce recommendations that drive executive decisions and open the door to the next engagement.
• Shape architecture: Serve as the senior technical authority on engagements, setting architectural direction, ensuring technical quality across the team, and making the calls that matter when tradeoffs are hard.
• Advise on ML operations: Help customers build ML systems they can actually own and sustain — translating MLOps, LLMOps, and production monitoring complexity into standards their engineering teams can execute and their leadership can act on.
• Drive pre-sales: Partner with sales and solutions teams during scoping and proposal phases, contributing the technical depth needed to scope work accurately and give prospects confidence in Caylent's ability to deliver.

Hands-On Delivery

• Lead engagements end-to-end: Drive architecture and solution design from kickoff through delivery — setting technical direction, unblocking the team on hard problems, and ensuring the work meets Caylent's quality standards.
• Own the technical relationship: Depending on the engagement, you are either the primary client contact owning all architect-level outcomes, or the senior technical authority providing oversight across the team. The expectation is the same in both cases — you are the person the engagement depends on technically.

Growing the Practice

• • Raise the bar internally: Mentor engineers and architects through real work, contribute to technical interviews, and build reference architectures and accelerators that make the broader ML practice better.

Your Qualifications (non-negotiables)

• 10+ years in machine learning or AI, with a proven track record of leading client-facing engagements in a consulting or advisory capacity.
• Demonstrated people management experience — hiring, performance calibration, career development, and the ability to have difficult conversations directly and constructively.
• Deep, current knowledge of the AWS ML and GenAI ecosystem, with the ability to make and defend architectural decisions across the full ML lifecycle — from data and feature engineering through training, deployment, and monitoring.
• Deep expertise in at least two or three ML domains — whether classical ML, computer vision, NLP, time series, or others — combined with the judgment to assess, architect, and advise across the broader ML landscape.
• Proven ability to architect and govern production ML systems end-to-end, translating MLOps, LLMOps, and broader AI operations complexity into standards that engineering teams can execute and executives can act on.
• Deep expertise across foundation model adaptation — fine-tuning (LoRA, QLoRA, PEFT), alignment (RLHF, DPO), inference optimization, and distributed training — combined with RAG and agentic system design, including multi-agent architectures, MCP integration, and human-in-the-loop patterns on AWS.
• Proven ability to operate independently in complex, ambiguous customer environments — navigating competing priorities, aligning stakeholders, and translating ML tradeoffs into business risk and value for both technical and executive audiences.

Strong differentiators

• AWS Certified Machine Learning – Specialty and/or AWS Certified Solutions Architect – Professional.
• Experience shaping practice-level standards, reference architectures, and reusable ML accelerators across multiple engagements.
• Exposure to varied industries and problem types in a consulting or client-facing context.
• Deep fluency in responsible AI practices — model evaluation, bias detection, fairness frameworks, and AI governance — applied in enterprise deployments.
• Fluency in AIOps patterns — designing agentic workflows for anomaly detection, automated root cause analysis, and remediation across observability platforms — and the ability to translate AI operations outcomes into measurable business value for customers.

Technical Stack

Our practice spans a broad range of ML domains. Candidates are expected to prescribe — not just recognize — with the judgment to maximize what AWS makes possible and the experience to know how open-source tooling strengthens it.

• ML Domains: Classical ML, Computer Vision, NLP, Generative AI & LLMs, AI Agents & Autonomous Systems, Intelligent Document Processing, Video Understanding, Speech & Audio, Time Series & Forecasting, Recommender Systems, Graph ML, Reinforcement Learning, Multimodal AI
• AWS ML Platform: SageMaker, SageMaker Pipelines, SageMaker Feature Store, SageMaker Model Registry, SageMaker Clarify, Bedrock (Agents, Knowledge Bases, Guardrails, AgentCore, Model Evaluation)
• Multi-provider LLM: Bedrock, Anthropic API, OpenAI API, Google Gemini API, Azure OpenAI — with the judgment to reason across provider tradeoffs in enterprise contexts
• AWS AI Services: Rekognition, Comprehend, Transcribe, Textract, Translate, Personalize, Neptune, Kinesis Video Streams, Polly
• Data Platform: Apache Spark / PySpark, Apache Kafka, Amazon Kinesis, Apache Iceberg, Delta Lake, Apache Hudi, AWS Glue
• Vector Databases: Pinecone, pgvector, Amazon OpenSearch (vector), Weaviate
• Frameworks: PyTorch, TensorFlow, JAX, Scikit-learn, XGBoost, HuggingFace (Transformers, PEFT, TRL), LangChain, LlamaIndex, DSPy, Ollama
• MLOps & Governance: MLflow, W&B, Airflow / MWAA (data orchestration), Dagster (asset-based pipelines), Kubeflow Pipelines, CI/CD, IaC (CloudFormation, CDK, Terraform), Docker, Kubernetes, ML Governance (lineage, data contracts, audit), Responsible AI / Bias & Fairness
• LLM Evaluation & Safety: RAGAS, LLM-as-judge patterns, DeepEval, NeMo Guardrails, Constitutional AI patterns, structured output validation
• Inference & Optimization: Triton, vLLM, SGLang, Trainium, Inferentia, Quantization (GPTQ, AWQ, bitsandbytes), SageMaker Neo

Benefits

• 100% remote work
• Medical Insurance for you and eligible dependents
• Generous holidays and flexible PTO
• Competitive phantom equity
• Paid for exams and certifications
• Peer bonus awards
• State of the art laptop and tools
• Equipment & Office Stipend
• Individual professional development plan
• Annual stipend for Learning and Development
• Work with an amazing worldwide team and in an incredible corporate culture

Important Information

Important Information

Experience: +7 years

Job Mode: Full-time

Work Mode: Remote

ID: 20891

Job Summary

We are seeking a highly experienced Senior IA Engineer with deep expertise in AI workloads, NLP, LLMs, and Voice APIs, along with strong hands-on experience in AWS and extensive use of Claude.

This role is ideal for someone who can design, build, and scale intelligent automation solutions powered by large language models and conversational AI. You will play a key role in architecting AI-driven systems, integrating voice capabilities, and optimizing model performance in production environments.

Responsibilities and Duties

• Design, develop, and deploy AI-driven solutions leveraging LLMs, NLP, and conversational AI technologies.
• Build and optimize voice-enabled applications using modern Voice APIs.
• Work extensively with Claude for prompt engineering, orchestration, and AI workflows.
• Develop scalable AI pipelines and services on AWS (e.g., Lambda, S3, SageMaker, Bedrock).
• Implement and maintain end-to-end AI workflows, from data ingestion to inference and monitoring.
• Fine-tune prompts, evaluate model outputs, and improve accuracy, latency, and cost efficiency.
• Collaborate with product and engineering teams to integrate AI capabilities into applications.
• Ensure security, governance, and compliance in AI systems.
• Monitor AI system performance and implement improvements based on real-world usage.
• Mentor team members and contribute to AI best practices and standards.

Qualifications and Skills

• 7+ years of experience in software engineering
• Strong hands-on experience with:
  • LLMs (Large Language Models) and NLP techniques
  • Claude (Anthropic) for building AI-driven applications
  • Voice APIs and speech-based interfaces
  • AWS cloud services (Lambda, S3, API Gateway, Bedrock, SageMaker, etc.)
• Experience designing and deploying AI workloads in production.
• Strong programming skills in Python (preferred) or similar languages.
• Experience with prompt engineering, evaluation frameworks, and model optimization.
• Understanding of REST APIs, microservices architecture, and distributed systems.
• Familiarity with data pipelines and handling structured/unstructured data.

Nice to have experience 

• Hands-on experience using Agentic AI to accelerate code implementation and enhance development productivity. 

• C++ knowledge and experience a benefit 

• Familiarity with cloud platforms and distributed computing: 

• Restful API design and implementation 

• AWS and Azure 

• Tools for scalable data processing: Kubernetes, Spark 

• Experience with Java 2D graphics or 3D OpenGL + CUDA programming. 

• Experience working with Cascading Style Sheets (CSS) 

About Encora 

Encora is a global company that offers Software and Digital Engineering solutions. Our practices include Cloud Services, Product Engineering & Application Modernization, Data & Analytics, Digital Experience & Design Services, DevSecOps, Cybersecurity, Quality Engineering, AI & LLM Engineering, among others. 

At Encora, we hire professionals based solely on their skills and do not discriminate based on age, disability, religion, gender, sexual orientation, socioeconomic status, or nationality. 

Important Information

Experience: +7 years

Job Mode: Full-time

Work Mode: Remote

ID: 19491

Job Summary

We are seeking a highly skilled and experienced Java UI Application developer  to lead the design, development, and optimization of advanced software solutions for geophysical data processing, modeling, visualization and interpretation. In this role, you will collaborate closely with geoscientists to create innovative tools that enhance data-driven decision-making through powerful visualization and interpretation capabilities. You will also collaborate with global development teams across Europe, Canada, and the United States, contributing to a dynamic and international engineering environment. 

Responsibilities and Duties

• Collaborate closely with a UX design team, product owners, and software engineers to translate UX requirements into robust GUI implementations with Eclipse RCP/SWT. 

• Present software designs and technical proposals to lead. 

• Ability to break down development tasks and lay out clear implementation roadmaps. 

• Implement and optimize computation algorithms  

• Design and develop both thin and thick client applications that interact with cloud-based microservices. 

• Working with complex UI Java threading and concurrency 

• Working with a large code base and multiple distributed development teams 

• Ensure high code quality through unit testing, code reviews, security hardening and continuous integration with other domain tools 

• Provide technical support and lead user troubleshooting sessions to resolve issues and ensure smooth operation of a complex RCP desktop application 

• Mentor junior developers and actively contribute to architectural and implementation decisions. 

• Embrace Agile/Scrum methodologies, delivering and demonstrating working solutions at the end of each sprint 

• Stay current with emerging technologies and trends in computing and software development.  

Qualifications and Skills

• BS or MS degree in computer science, Geoscience, Applied Mathematics, or a related engineering discipline. 

• Ability to break down complex development tasks and define clear, actionable implementation of roadmaps. 

• Proficiency with development tools and environments: 

• Preferred strong Java experience 

• GitLab/Github, Eclipse RCP/SWT, VS Code, CI/CD pipelines 

• Performance tools: VisualVM, JMC/JFR, Async 

• Operating systems: Windows and Linux 

• Must be self-motivated and able to work well in a distributed team environment 

• Experience developing commercial thick client desktop applications 

Nice to have experience 

• Hands-on experience using Agentic AI to accelerate code implementation and enhance development productivity. 

• C++ knowledge and experience a benefit 

• Familiarity with cloud platforms and distributed computing: 

• Restful API design and implementation 

• AWS and Azure 

• Tools for scalable data processing: Kubernetes, Spark 

• Experience with Java 2D graphics or 3D OpenGL + CUDA programming. 

• Experience working with Cascading Style Sheets (CSS) 

About Encora 

Encora is a global company that offers Software and Digital Engineering solutions. Our practices include Cloud Services, Product Engineering & Application Modernization, Data & Analytics, Digital Experience & Design Services, DevSecOps, Cybersecurity, Quality Engineering, AI & LLM Engineering, among others. 

At Encora, we hire professionals based solely on their skills and do not discriminate based on age, disability, religion, gender, sexual orientation, socioeconomic status, or nationality. 

Our mission is to turn students and recent graduates into world-class software engineers in just a few months.

We aim to help you find a job at Encora and build a better career path.

Our program equips you with the essential skills to navigate real-life scenarios that you can later apply with larger teams and clients

------------------------

What is AWS re/Start?

A free, cohort-based training program that helps students launch careers in the cloud.

It prepares learners for entry to mid-level cloud roles through hands-on, real-world training and professional skills development, and connects them with potential employers.

------------------------

Requirements

• A) Being at least in the middle of your career or a recent graduate of IT-related careers, such as Software Development, Mechatronics, or other related fields.  
  • B) Or having some experience with programming (at least six months), please include your personal projects in your resume besides the boot camps, workshops, courses you might have taken, etc.  
• English B1/B2.  
• Internships don't count as working experience, but please include them in your resume.  
• Have at least five hours available during the day.  
• Mexican nationality or permanent resident. (We're not currently accepting candidates living in other countries).
• Successfully pass the selection process. 

Benefits of being part of the program.

- Cloud Computing Training

- Professional Practice hours

- AWS Certification Voucher 

- Direct Access to Spark Program

We strongly recommend constantly reviewing your inbox and spam email. 

Encora is an equal-opportunity employer committed to fostering, cultivating, and preserving a culture of diversity, equality, and inclusion. 

We embrace and encourage our employees and applicants/candidates' differences in age, color, disability, ethnicity, family or marital status, gender identity and/or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socioeconomic status, veteran status, and other characteristics that make our employees unique. 

Every individual has the right to work in a professional atmosphere that promotes equal employment opportunities and prohibits discriminatory practices, including harassment of any kind.

Data Analyst Std

Responsabilidades

·        Recopilar, organizar, analizar y difundir cantidades significativas de información con atención al detalle para garantizar la calidad e integridad de los datos.

·        Desarrollar, automatizar, verificar y monitorear proyectos para los análisis orientados a las necesidades de negocio.

·        Mejora continua del proceso de análisis de datos e infraestructura.

·        Generar insights identificando e interpretando tendencias o patrones en conjuntos de datos con la finalidad de apoyar a negocio con la toma de decisiones basadas en datos.

·        Diseñar sistemas de reporting para la visualización de informes periódicos que resuman el análisis de los datos.

·        Elaborar vistas y dashboards para proporcionar información útil a negocio.

Skill

·        AWS Redshift

·        Jira

·        Paquetería de Microsoft Office

·        Tableau/Power BI

Lenguajes de programación

·        SQL

·        Python (Pandas, Spark)

Manejo de metodología/filosofía Ágil deseable     

·        Scrum  

·        Kanban

Idiomas Nivel de inglés intermedio

Soft Skills

·        Comunicación efectiva con stakeholder clave y líderes de negocio.              

·        Capacidad analítica y organizacional superior.      

·        Enfoque en resultados con alta capacidad de ejecución.  

·        Precición y atención al detalle.    

·        Adaptabilidad proactiva al campo y apertura a retroalimentación.

·        Capacidad de autoaprendizaje y mejora continua

·        Gestión de proyectos      

·        Trabajo en equipo con enfoque en sinergia organizacional 

Requisitos:

·        Escolaridad         

·        Ing. Sistemas Computacionales  Economía

·        Matemáticas      Actuaría

·        Estadística      

Asignación hibrida, hay que acudir a sitio 3 veces por semana (Reforma, CDMX)

We are looking for a hands-on Senior Data Engineer to join a small team (2 Data Engineers + 1 Data Analyst). You will help scale our AWS-based data infrastructure, working primarily with industrial data sources and high-volume time-series data.

Responsibilities Will Include:  

• Engage directly with end users to understand how they consume data, and design solutions that serve their needs.
• Design, develop, and maintain scalable ETL/ELT pipelines for batch and real-time processing, including high-frequency time-series ingestion.
• Evolve the Data Lakehouse—optimizing storage, performance, and data consistency.
• Manage orchestration workflows with complex dependencies and error handling.
• Implement data governance, security controls, and audit policies across the AWS ecosystem, leveraging services such as AWS Lake Formation for centralized data lake permissions and governance.
• Optimize performance and cost (FinOps); identify and resolve technical bottlenecks.
• Partner with the Data Analyst to deliver production-ready, analytics-optimized datasets.
• Build monitoring, alerting, and data quality testing for platform reliability.

Requirements:

• Bachelor’s degree in Computer Science, Computer Engineering, or a closely related discipline is required.
• At a minimum, 5+ years of experience in Data Engineering, Analytics Engineering, or related roles.
• Deep hands-on experience with core AWS data services: Glue, Athena, Step Functions, Lambda, Kinesis, and Lake Formation.
• Hands-on experience with Apache Iceberg (required).
• Expert proficiency in Python (PySpark / Python Shell) and advanced SQL (window functions, CTEs, execution plan tuning).
• Solid grasp of ETL/ELT tooling and dimensional modeling best practices (Kimball).
• Experience preparing data architectures for visualization tools and operational/management reporting.
• Practical experience with NoSQL engines (e.g., DynamoDB) and relational SQL databases.
• Infrastructure as Code: Terraform or AWS CloudFormation.

Preferred Experience:

• Apache Airflow (MWAA experience preferred) or native AWS orchestration.
• Familiarity with dbt, Airbyte, or Fivetran.
• Experience automating CI/CD for Glue jobs or Lambda deployments.

Soft Skills:

• Senior peer mindset—leads through code reviews and mentorship, not hierarchy.
• Pragmatic decision-maker who picks the right tool for cost, efficiency, and project needs.
• Strong ownership of end-to-end data quality and system availability.
• Clear communicator who can translate business needs into technical solutions. 

Note: This isn’t an active role right now, but we’re building a community of great talent for future opportunities at Caylent. If your background aligns with what we’re looking for, our team may reach out to learn more about you and explore potential future fits.

The Mission

At Caylent, a Senior Machine Learning Engineer works as an integral part of a cross-functional delivery team to design and document machine learning solutions on the AWS cloud for our customers.  We are looking for someone that has a strong understanding of the various model types and tools, and can help our customers connect their business goals with the details of feature design, model training and inference.  You will develop solutions designed by an architect.

You will participate in daily standup meetings with your team and bi-weekly agile ceremonies with the customer.  Your manager will have a weekly 1:1 with you to help guide you in your career and make the most of your time at Caylent.

Your Assignments

• Work with a team to deliver machine learning solutions on AWS for customers
• Participate in and contribute to daily standup meetings
• Develop and implement ML models, MLOps, and analytics
• Big data processing and preparation of training data for models

Your Qualifications

• Strong experience in building ML models for real world applications
• Strong experience in at least one of these:
• AWS ML Services/SageMaker
• ML libraries like Keras, Tensorflow, PyTorch, Scikit-learn
• MLOps tools such as MLflow, Kubeflow, Airflow
• Advanced analytics using time series forecasting and/or inferential statistics
• Strong experience in one or more of these data processing solutions:
• Big data processing platforms like Spark, Hadoop, or streaming platforms
• Data processing and cleansing using Python/Pandas, PySpark, Scala, SQL
• Strong understanding of feature definition, model meta-data, hyperparameter tuning, stochastic gradient descent, deep learning layer types and activation functions
• Experience in visualization using SageMaker, ggplot, matplotlib, or seaborn
• Experience with an IaC tool such as CloudFormation, Amazon CDK or Terraform
• Excellent written and verbal communication skills

Benefits 

• 100% remote work
• Medical Insurance for you and eligible dependents
• Generous holidays and flexible PTO
• Competitive phantom equity
• Paid for exams and certifications
• Peer bonus awards
• State of the art laptop and tools
• Equipment & Office Stipend
• Individual professional development plan
• Annual stipend for Learning and Development
• Work with an amazing worldwide team and in an incredible corporate culture

This role may require up to 25% travel, depending on business needs.