We’re looking for a Senior Data Engineer to design, build, and operate the data pipelines and aggregates that power Zeta’s AdTech platform. This is a hands-on individual contributor role focused on high-scale batch + streaming data processing, reliable data products, and analytics-ready datasets that enable prediction, agentic workflows, BI reporting, and measurement. You will partner closely with backend, ML, and product teams to deliver trusted, well-modeled data with strong performance, quality, and observability.

What You’ll Do

• Build data pipelines: Develop robust batch and streaming pipelines (Kafka/Kinesis) to ingest, transform, and enrich large-scale event data (impressions, clicks, conversions, costs, identity signals).
• Create data aggregates & marts: Design and maintain curated aggregates and dimensional models for multiple consumers—prediction models, agents, BI dashboards, and measurement workflows.
• Data modeling & contracts: Define schemas, data contracts, and versioning strategies to keep downstream systems stable as sources evolve.
• Data quality & reliability: Implement validation, anomaly detection, backfills, and reconciliation to ensure completeness, correctness, and timeliness (SLAs/SLOs).
• Performance & cost optimization: Optimize compute/storage for scale (partitioning, file sizing, incremental processing, indexing), balancing latency, throughput, and cost.
• Orchestration & automation: Build repeatable workflows with scheduling/orchestration (e.g., Airflow, Dagster, Step Functions) and CI/CD for data pipelines.
• Observability for data systems: Instrument pipelines with metrics, logs, lineage, and alerting to accelerate detection and root-cause analysis of data issues.

Security & governance: Apply least-privilege access, PII-aware handling, and governance controls aligned with enterprise standards.

5+ years building production data pipelines and data products (batch and/or streaming) in a high-scale environment.

Strong experience with SQL and data modeling (dimensional modeling, star/snowflake schemas, event modeling).

• Hands-on experience with streaming systems (Kafka preferred) and/or AWS Kinesis, including event-driven designs.
• Proficiency in one or more languages used for data engineering (Python, Java, Scala, or Go).
• Experience with distributed data processing (Spark, Flink, or equivalent) and performance tuning at scale.
• Experience with AWS data services and cloud-native patterns (S3, Glue/EMR, Athena, Redshift, etc. as applicable).
• Familiarity with lakehouse/table formats and large-scale storage patterns (e.g., Parquet; Iceberg/Hudi/Delta are a plus).
• Experience with orchestration/workflow tooling (Airflow/Dagster/Step Functions) and CI/CD for data workloads.
• Strong data quality/observability practices (tests, monitoring, lineage; understanding of SLAs/SLOs).
• Experience with SQL + NoSQL data stores (e.g., Postgres/MySQL; DynamoDB/Cassandra/Redis) and choosing the right store per use case.

Clear communicator and collaborator; able to work with mixed audiences and translate needs into reliable data interfaces.

• AdTech / programmatic advertising domain knowledge: DSP/SSP/exchange/RTB concepts and data flows.
• Experience building measurement pipelines (attribution, incrementality, lift, or experimentation analytics).

Experience supporting ML feature stores, offline/online feature generation, or model training datasets.

• Experience with real-time analytics stores (Druid/ClickHouse/Pinot) and high-cardinality aggregation strategies.
• Deep knowledge of data governance/privacy, including PII handling and consent-aware data processing.
• Open-source contributions, publications, or conference speaking.
• BS/MS in CS/Engineering or equivalent practical experience.

WHO WE ARE 

Zeta Global (NYSE: ZETA) is the AI-Powered Marketing Cloud that leverages advanced artificial intelligence (AI) and trillions of consumer signals to make it easier for marketers to acquire, grow, and retain customers more efficiently. Through the Zeta Marketing Platform (ZMP), our vision is to make sophisticated marketing simple by unifying identity, intelligence, and omnichannel activation into a single platform – powered by one of the industry’s largest proprietary databases and AI. Our enterprise customers across multiple verticals are empowered to personalize experiences with consumers at an individual level across every channel, delivering better results for marketing programs. Zeta was founded in 2007 by David A. Steinberg and John Sculley and is headquartered in New York City with offices around the world. To learn more, go to www.zetaglobal.com.

PEOPLE & CULTURE AT ZETA

Zeta considers applicants for employment without regard to, and does not discriminate on the basis of an individual’s sex, race, color, religion, age, disability, status as a veteran, or national or ethnic origin; nor does Zeta discriminate on the basis of sexual orientation, gender identity or expression.  

We’re committed to building a workplace culture of trust and belonging, so everyone feels invited to bring their whole selves to work. We provide a forum for employees to celebrate, support and advocate for one another. Learn more about our commitment to diversity, equity and inclusion here:  https://zetaglobal.com/blog/a-look-into-zetas-ergs/ 

ZETA IN THE NEWS!

https://zetaglobal.com/press/?cat=press-releases 

The Community You Will Join:

The Guest & Host team based out of India, operates to ensure high quality supply and merchandising differentiates our brand, by providing tools to be used by 1000+ operations agents for supply vetting and quality moderation. As Airbnb expands beyond the core, it is looking to onboard supply outside of the core stays business which requires enhancing our tools. The operational tasks we face are diverse and rapidly evolving. The current manual processes and lack of optimum tooling capabilities hinder the ability of operation agents to work more efficiently, maintain business continuity, and achieve higher scale. 

The Difference You Will Make:

As a Data Engineer on the Guest & Host team, you will play a pivotal role in shaping the systems that onboard and manage the highest quality supply across Airbnb. You’ll build robust data pipelines and platforms that power end-to-end visibility for supply operations, from onboarding and regulatory compliance to AI-assisted vetting and listing quality enforcement. Your work will directly enable operations, product, and ML teams to scale trusted supply globally, ensuring every home, service, and experience meets Airbnb’s standards. Whether it’s surfacing insights to optimize onboarding flows, enabling smarter audit triggers, or supporting nuanced licensing workflows, your contributions will be foundational to helping hosts join Airbnb efficiently and ensuring guests have access to safe, high-quality stays.
As you build and maintain key components of the critical data ecosystem, you’ll have the opportunity to contribute to creating standards and best practices for Airbnb’s Data Engineering. Your work on solving complex business challenges at scale will be instrumental in shaping the tools, processes, and standards used by the broader data community.

A Typical Day:

• Design, build, and maintain robust and efficient data pipelines that collect, process, and store data from various sources, including user interactions, listing details, and external data feeds.
• Develop data models that enable the efficient analysis and manipulation of data for merchandising optimization. Ensure data quality, consistency, and accuracy.
• Build scalable data pipelines (SparkSQL & Scala) leveraging Airflow scheduler/executor framework
• Collaborate with cross-functional teams, including Data Scientists, Product Managers, andSoftware Engineers, to define data requirements, and deliver data solutions that drive merchandising and sales improvements.
• Contribute to the broader Data Engineering community at Airbnb to influence tooling and standards to improve culture and productivity
• Improve code and data quality by leveraging and contributing to internal tools to automatically detect and mitigate issues

Your Expertise:

• 6+ years of relevant industry experience 
• BE/B.tech in computer science or relevant technical field
• Extensive experience designing, building, and operating robust distributed data platforms (e.g., Spark, Kafka, Flink, HBase) and handling data at the petabyte scale.
• Strong knowledge of Java, Scala, or Python, and expertise with data processing technologies and query authoring (SQL).
• Demonstrated ability to analyze large data sets to identify gaps and inconsistencies, provide data insights, and advance effective product solutions
• Expertise with ETL schedulers such as Apache Airflow, Luigi, Oozie, AWS Glue or similar frameworks
• Solid understanding of data warehousing concepts and hands-on experience with relational databases (e.g., PostgreSQL, MySQL) and columnar databases (e.g., Redshift, BigQuery, HBase, ClickHouse)
• Excellent written and verbal communication skills

At Reltio®, we believe data should fuel business success. Reltio’s AI-powered data unification and management capabilities—encompassing entity resolution, multi-domain master data management (MDM), and data products—transform siloed data from disparate sources into unified, trusted, and interoperable data. Reltio Data Cloud™ delivers interoperable data where and when it's needed, empowering data and analytics leaders with unparalleled business responsiveness. Leading enterprise brands—across multiple industries around the globe—rely on our award-winning data unification and cloud-native MDM capabilities to improve efficiency, manage risk and drive growth.

At Reltio, our values guide everything we do. With an unyielding commitment to prioritizing our “Customer First”, we strive to ensure their success. We embrace our differences and are “Better Together” as One Reltio. We are always looking to “Simplify and Share” our knowledge when we collaborate to remove obstacles for each other. We hold ourselves accountable for our actions and outcomes and strive for excellence. We “Own It”. Every day, we innovate and evolve, so that today is “Always Better Than Yesterday”. If you share and embody these values, we invite you to join our team at Reltio and contribute to our mission of excellence.

Reltio has earned numerous awards and top rankings for our technology, our culture and our people. Reltio was founded on a distributed workforce and offers flexible work arrangements to help our people manage their personal and professional lives. If you’re ready to work on unrivaled technology where your desire to be part of a collaborative team is met with a laser-focused mission to enable digital transformation with connected data, let’s talk!

Job Summary:

As a Staff Full-Stack Engineer at Reltio, you will be a key member of our new Data Quality team, responsible for building a cutting-edge Data Observability platform from scratch. This platform will provide automated profiling and anomaly detection across various data sources, including Cloud Data Warehouses (Snowflake, BigQuery, Databricks, Redshift), dbt, Kafka/streaming, and SaaS applications (SFDC/Dynamics). You will contribute to both the API and UI development, ensuring a robust and intuitive experience. This is an individual contributor role.

Job Duties and Responsibilities:
(IC: Knowledge | Leadership | Communication)
(MGR: Knowledge | People Management & Leadership | Strategic Impact)
● Design, develop, and maintain the Data Observability platform using Python for the agentic and backend services.
● Implement robust and scalable APIs for seamless integration with various data sources
● Collaborate with frontend engineers on UI design and contribute to UI development as needed.
● Collaborate with cross-functional teams to define requirements, design solutions, and ensure the successful delivery of the platform.
● Contribute to the entire software development lifecycle, from conceptualization and design to deployment and ongoing maintenance
● Ensure the platform's performance, reliability, and security through rigorous testing and adherence to best practices
● Mentor junior/middle engineers and contribute to a culture of technical excellence and continuous improvement.

Skills You Must Have:
● 7+ years of experience in enterprise software development, building scalable backend platforms.
● Expert hands‑on experience developing backend services and platform APIs using Python (e.g., FastAPI, Flask, Django).
● Proven track record of delivering high‑quality enterprise SaaS platforms in high‑stakes environments.
● Experience delivering SaaS applications that scale and perform with low latency and high throughput.
● Strong written and verbal communication skills. Proven track record of unit and integration testing with CI/CD as part of your development process.
● Experience working with AI and automation tools to improve productivity and delivery speed (GitHub Copilot, Claude Code, Cursor, VSCode Kilo Code, etc.)

Skills That Are Nice to Have:
● Familiarity with cloud-based development using AWS, Google Cloud Platform (GCP), and/or Microsoft Azure services (such as Lambda, S3, Pub/Sub, Dataflow, or Azure Functions)
● Ability to deliver modern, intuitive UI/UX using React.js (and optionally TypeScript) with minimal guidance.
● Background in Data Quality systems, frameworks, or tools (e.g., profiling, validation, monitoring)
● Experience or understanding of Master Data Management (MDM) concepts, data modeling, and enterprise data integration patterns
● Exposure to containerization and orchestration technologies (Docker, Kubernetes)
● Familiarity with monitoring and observability stacks (Mezmo, Grafana, etc.)

About the Role

We’re looking for an experienced Senior Marketing Operations Manager to oversee the delivery and analysis of Ethos’ CRM lifecycle campaigns, with an emphasis on email and SMS campaign execution. The ideal candidate is a thought partner for innovative use of experimentation, technology, data, and insights to drive campaign efficiency and effectiveness. You will also play a role in ensuring our Marketing/CRM capabilities are continuously evolving to meet the ongoing needs of the business and our customers. The position will work closely with all parts of the business to execute CRM deployment strategies that move business metrics.

This is a technical role that requires a blend of hands-on execution and longer-term, strategic planning. At Ethos, our offline experiences (email, SMS, direct mail, interactions with insurance agents) are all valuable touchpoints that we consider to be part of the core user experience. We’re looking for someone who is a consumer-first expert in email and SMS deployment strategy with meticulous attention to detail. This role will report into Ethos’ head of Partnership Lifecycle Marketing.

Duties and Responsibilities:

• Attend project kick offs and be involved in briefs to architect solutions prior to building
• Clarify, capture, and optimize requirements in order to build ad-hoc and automated communications
• Build, schedule, launch, and monitor complex automated and ad-hoc campaigns across email, SMS, and direct mail to drive new members through the insurance application process
• Setting up and monitoring complex journeys, and automations that have static/dynamic content with actionable trigger points to drive conversion and engagement
• Script dynamic communications to build a personalized user experience
• Write SQL to manage/build data tables, and build custom audience segmentation
• Maintaining and developing audience segmentation tactics by proactively guiding our team’s data pipeline and data needs
• Establishing high quality processes and infrastructure for our email and SMS tooling
• Codifying documentation of internal best practices, tooling, and process improvements

Qualifications and Skills:

• Deep experience using Iterable, Marketo or similar email management software
• Email and SMS deployment experience leveraging scripting languages (liquid template language) and concepts
• Extremely high attention to detail, all while managing a large volume of campaigns simultaneously
• Process oriented mindset that excels in structured workflows around testing, QA, and stakeholder approvals to improve execution efficiency and reduce errors.
• Strong analytical skills, competence in SQL, and experience with tools for doing data analysis i.e. Mode, Chartio, Redshift, Heap
• Strong collaboration skills in team environments, ability to effectively work with key stakeholders to clarify campaign requirements, but able to act quickly as the decision-maker
• High technical aptitude with the ability to quickly ramp up on internal nuances related to people, processes, and technology.
• A minimum of 4 years of experience building cross-channel campaigns using ESP platforms and/or marketing automation platforms
• Experience in launching audience-specific dynamic content lifecycle and event-triggered CRM programs
• Working familiarity with HTML/CSS
• Comfort with data pipelines and architecture, targeting, multi-step workflows, QA, and reporting
• Strong knowledge of best practices for email creative, segmentation, dynamic content, testing methodologies, deliverability, CAN-SPAM regulations, email deployment platforms, and ESPs
• Knowledge of the interconnectivity between technology and customer experience
• Ability to compile a well-articulated dashboard and share performance metrics
• Excellent project management skills, ability to multitask effectively, and work cross-functionally

#LI-ND1
#LI-Hybrid

About Netradyne:

Netradyne provides AI-powered technologies for fleet management and safer roads. An award-winning industry leader in fleet safety and video telematics solutions, Netradyne empowers thousands of commercial fleet customers across North America, Europe, and Asia to enhance their driver performance, reduce risk, and optimize operations.

Netradyne sets the standard among transportation technology companies for enhancing and sustaining road safety, with an industry-leading 25+ billion miles vision-analyzed for risk and an industry-first driver scoring system that reinforces safe behaviors. Founded in 2015, Netradyne is headquartered in San Diego with offices in San Francisco, Nashville, the UK and Bangalore. For more details visit: www.netradyne.com

Job Overview:

As a Staff Data Engineer – ML at Netradyne, an award-winning industry leader in fleet safety and video telematics solutions, you will take senior technical ownership of the machine learning and data platforms that underpin our AI-powered fleet analytics. This role is responsible for designing, building, and scaling production-grade ML pipelines, generative AI capabilities, and real-time data streaming systems across cloud and edge environments, delivering actionable insights that make fleet operations safer and more efficient. You will collaborate closely with machine learning engineers, data scientists, and product teams to integrate advanced AI technologies into Netradyne's platform, including on-device edge intelligence and natural-language-driven capabilities. Your work will directly shape the data infrastructure behind Netradyne's Physical AI vision, where AI continuously interprets multimodal vehicle data to understand drivers, vehicles, and road environments as an integrated system.

Key Responsibilities:

• You will be embedded within a team of machine learning engineers and data scientists, responsible for building and productising generative AI, deep learning, and data engineering solutions. You will:
• Design, develop and deploy production-ready, scalable solutions that utilise generative AI, traditional ML models, data science workflows, and ETL/ELT pipelines on AWS cloud infrastructure (and hybrid edge-cloud environments).
• Build and manage real-time and batch data streaming pipelines to handle high-volume, high-velocity data from fleet devices, leveraging technologies such as Apache Kafka and Amazon Kinesis for low-latency processing and near real-time insights.
• Collaborate with cross-functional teams (Product, Data Science, ML Engineering, Operations) to integrate AI-driven solutions into business operations and customer-facing products.
• Design and implement generative AI solutions using large language models (LLMs), including prompt engineering, fine-tuning, and retrieval-augmented generation (RAG) patterns, to enable intelligent analytics, natural-language interfaces, and context-aware insights across fleet and safety data.
• Build and scale agentic AI systems by developing autonomous and semi-autonomous agents that orchestrate data retrieval, reasoning, and actions across ML pipelines and services, ensuring these agentic workflows are production-grade, observable, and aligned with safety, reliability, and governance requirements.
• Implement MLOps best practices including CI/CD pipelines for model training, automated testing, model versioning, continuous monitoring, and modern workflow orchestration (e.g. Apache Airflow, MLFlow) to achieve reliable, reproducible model deployments at scale.
• Champion data quality and governance by implementing data contracts, rigorous validation, and monitoring to ensure that analytical pipelines meet defined SLAs and that downstream models and business users can trust the data.
• Conduct research and stay current with the latest advancements in generative AI, vector search techniques, LLM frameworks, orchestration platforms, and related technologies.

Mandatory Skills:

• Experience with data visualisation and BI tools (e.g. Tableau, Grafana, Plotly Dash).
• Exposure to real-time data streaming and messaging systems (e.g. Apache Kafka, Amazon Kinesis, Amazon SQS).
• Knowledge of containerisation and orchestration (e.g. Docker, Kubernetes/EKS)
• Strong understanding of generative AI system design, including prompt engineering, RAG architectures, vector search, and evaluation techniques for LLM-based applications in production environments.
• Experience with agentic AI patterns, such as designing, orchestrating, and monitoring autonomous or semi-autonomous agents that coordinate tools, data sources, and ML services with appropriate safety, observability, and governance controls.
• Experience with modern workflow orchestration platforms such as Apache Airflow, Prefect, or Dagster for scheduling and managing complex ETL/ML pipelines. These tools are now standard for data pipeline engineering.
• Proficiency with at least one Python web framework (e.g. FastAPI, Django, Flask) for developing data or model-serving APIs.
• Experience with rapid prototyping tools (e.g. Streamlit, Gradio, Dash) for demonstrating ML solutions to stakeholders.
• Familiarity with modern ML frameworks and libraries such as PyTorch, TensorFlow, and Hugging Face Transformers
• Background in large-scale data processing and lakehouse or data warehousing technologies (e.g. Snowflake, Amazon Redshift, Apache Spark/EMR, Delta Lake).

Qualifications and Education Requirements:

• B.Tech, M.Tech or PhD in Computer Science, Data Science, Electrical Engineering, Statistics, Mathematics, Operations Research, or a related field (or equivalent professional experience).
• 5–8 years of industry experience in data engineering, machine learning engineering, or related roles, with a track record of building and scaling data/ML solutions in production.
• Strong programming skills in Python and SQL, with solid fundamentals in algorithms, data structures, and object-oriented programming.
• Experience building end-to-end solutions on AWS cloud infrastructure including developing data pipelines (ETL/ELT), deploying ML models at scale, and utilising cloud services (e.g. S3, Lambda, EKS).
• In-depth understanding of data storage systems: proficient with relational databases (SQL), NoSQL datastores, and modern vector databases, including schema design and query optimisation for large-scale datasets.
• Hands-on experience with generative AI tools and workflows, and practical work with large language models (LLMs), including building LLM-powered applications and utilising RAG techniques to incorporate external knowledge.
• Working knowledge of MLOps principles and tools — e.g. model lifecycle management, CI/CD pipelines for ML, automated data/feature pipelines, and monitoring/alerting for deployed models.
• Strong analytical and problem-solving skills with keen attention to detail.
• Solid foundation in statistics, probability, and estimation theory.
  
  

Equal Opportunity Employer Statement:
Netradyne is an equal opportunity employer and are committed to creating an inclusive environment for all employees.

What You Will Do and Learn

As a Snowflake Architect/ Manager in Data Solutions, you’ll be responsible for designing, implementing, and testing proposed modern analytic solutions.  Working closely with our client partners and architects, you’ll develop relationships with key technical resources while delivering tangible business outcomes. 

• Manage the Data engineering lifecycle including research, proof of concepts, architecture, design, development, test, deployment, and maintenance
• Collaborate with team members to design and implement technology that aligns with client business objectives
• Build proof of concepts for a modern analytics stack supporting a variety of Cloud-based Business Systems for potential clients
• Team management experience and ability to manage, mentor and develop talent of assigned junior resources
• Create actionable recommendations based on identified platform, structural and/or logic problems
• Communicate and demonstrate a clear understanding of client business needs, goals, and objectives
• Collaborate with other architects on solution designs and recommendations.

Qualifications:

• 8+ years’ experience developing industry leading business intelligence and analytic solutions
• Must have thorough knowledge of data warehouse concepts and dimensional modelling
• Must have experience in writing advanced SQL
• Must have at least 5+ years of hands-on experience on DBT (Data Build Tool). Mandatory to have most recent hands-on experience on DBT.
• Must have experience working with DBT on one or more of the modern databases like Snowflake / Amazon Redshift / BigQuery / Databricks / etc.
• Hands-on experience with Snowflake would carry higher weightage
• Snowflake SnowPro Core certification would carry higher weightage
• Experience working in AWS, Azure, GCP or similar cloud data platform would be an added advantage
• Hands-on experience on Azure would carry higher weightage
• Must have experience in setting up DBT projects
• Must have experience in understanding / creating / modifying & optimizing YML files within DBT
• Must have experience in implementing and managing data models using DBT, ensuring efficient and scalable data transformations
• Must have experience with various materialization techniques within DBT
• Must have experience in writing & executing DBT Test cases
• Must have experience in setting up DBT environments
• Must have experience in setting up DBT Jobs
• Must have experience with writing DBT Jinja and Macros
• Must have experience in creating DBT Snapshots
• Must have experience in creating & managing incremental models using DBT
• Must have experience with DBT Docs
• Should have a good understanding of DBT Seeds
• Must have experience with DBT Deployment
• Must Experience with architecting data pipelines using DBT, utilizing advanced DBT features
• Proficiency in version control systems and CI/CD
• Must have hands-on experience configuring DBT with one or more version control systems like Azure DevOps / Github / Gitlab / etc.
• Must have experience in PR approval workflow
• Participate in code reviews and best practices for SQL and DBT development
• Experience working with visualization tools such as Tableau, PowerBI, Looker and other similar analytic tools would be an added advantage
• 2+ years of Business Data Analyst experience
• 2+ years of experience writing Business requirements, Use cases and/or user stories, for data warehouse or data mart initiatives.
• Understanding and experience on ETL/ELT is an added advantage
• 2+ years of consulting experience working on project-based delivery using Software Development Life Cycle (SDLC)
• 2+ years of years of experience with relational databases (Postgres, MySQL, SQL Server, Oracle, Teradata etc.)
• 2+ years of experience creating functional test cases and supporting user acceptance testing
• 2+ years of experience in Agile/Kanban/DevOps Delivery
• Outstanding analytical, communication, and interpersonal skillsAbility to manage projects and teams against planned work
• Responsible for managing the day-to-day client relationship on projects

Title: Principal Data Software Engineer

Location: Bengaluru (Bangalore)

Opportunity:

Get Well is seeking a visionary and technically adept Principal Data Software Engineer to design, develop and optimize our cloud-native data platform supporting AI, analytics, and clinical applications. This role is pivotal in architecting scalable, secure, and high-performance data processing systems within a regulated healthcare environment. 

The ideal candidate brings deep technical expertise in data engineering, data governance, cloud infrastructure and hands-on experience with healthcare data standards, EMR integration, and clinical ontologie. The candidate should have a proven record of building secure, scalable data platforms. This position reports to the Senior Director, Product Development. This role requires close collaboration with data engineers, product teams, AI engineers and compliance specialists to deliver accurate, accessible, and actionable data solutions.

Responsibilities:

Platform Architecture & Design

• Design and implement scalable, secure, and efficient data architectures (e.g., data lakehouse, medallion architecture) to support enterprise AI and analytics initiatives.
• Define technical specifications for data ingestion, transformation, storage, and access layers.
• Evaluate and recommend tools, frameworks, and cloud infrastructure to optimize performance, scalability, and cost-efficiency.
• Ensure architectural alignment with organizational AI, analytics, and clinical application goals.

Data Engineering & Operations

• Develop and maintain high-performance data pipelines for both batch and streaming data processing, leveraging tools such as Apache Spark, Databricks or Snowflake.
• Implement deployment and orchestration frameworks (e.g., Airflow, dbt, Spark, Databricks, Snowflake)
• Adhere to engineering best practices for CI/CD, observability, incident response, and SLA adherence
• Optimize data processing systems for performance, reliability, and reusability.

• Mentor engineers to foster technical growth and ensure alignment with best practices in data engineering.

Governance, Quality & Compliance

• Collaborate with data governance and compliance teams to implement data security, encryption, and access control policies in line with HIPAA, GDPR, and other regulations.
• Ensure data quality through validation, lineage tracking, and metadata management practices.
• Support the development and maintenance of data catalogs for discoverability and stewardship

Collaboration & Technical Leadership

• Partner with data engineers, product teams, and clinical informatics specialists to deliver integrated data solutions.
• Provide technical guidance and mentorship to junior engineers, fostering a culture of technical excellence and collaboration.
• Communicate complex technical designs and solutions to both technical and non-technical stakeholders effectively.
• Contribute to agile development practices, participating in code reviews, design discussions, and continuous improvement initiatives.

Innovation & Technical Expertise

• Stay informed about emerging trends in data engineering, cloud-native architectures, and healthcare data standards.
• Prototype and evaluate modern data frameworks and tools (e.g., Delta Lake, Apache Iceberg) to enhance platform capabilities.
• Communicate complex technical concepts to both technical and non-technical stakeholders.
• Advocate for best practices in data platform design to ensure scalability, explainability, and compliance in AI-driven systems.

Requirements:

Education & Experience

• Bachelor’s or Master’s degree in Computer Science or related technical discipline
• 12+ years of experience with at least 4+ years in data engineering or platform roles
• Proven track record of designing and implementing cloud-native data processing systems.

Technical Proficiency

• Advanced proficiency in Python, Scala, SQL, and distributed data processing frameworks such as Apache Spark.
• Hands-on experience with cloud-based data platforms (e.g., Databricks, Snowflake, BigQuery, or Redshift).
• Demonstrated ability to transform raw clinical data into curated, ML-ready datasets for analytics and AI applications.
• Hands-on expertise in healthcare data standards including FHIR, HL7, USCDI, and CCDA

Professional Skills

• Strong problem-solving skills with a focus on delivering scalable and maintainable solutions.
• Excellent collaboration and communication skills, with the ability to work effectively in cross-functional teams.
• Proactive, detail-oriented, and committed to driving technical excellence in a fast-paced environment.

About Get Well:

Now part of the SAI Group family, Get Well is redefining digital patient engagement by putting patients in control of their personalized healthcare journeys, both inside and outside the hospital. Get Well is combining high-tech AI navigation with high-touch care experiences driving patient activation, loyalty, and outcomes while reducing the cost of care. For almost 25 years, Get Well has served more than 10 million patients per year across over 1,000 hospitals and clinical partner sites, working to use longitudinal data analytics to better serve patients and clinicians. AI innovator SAI Group led by Chairman Romesh Wadhwani is the lead growth investor in Get Well. Get Well’s award-winning solutions were recognized again in 2024 by KLAS Research and AVIA Marketplace. Learn more at Get Well and follow-us on LinkedIn and Twitter.

Get Well is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age or veteran status.

About SAI Group:

• SAIGroup commits to $1 Billion capital, an advanced AI platform that currently processes 300M+ patients, and 4000+ global employee base to solve enterprise AI and high priority healthcare problems. SAIGroup - Growing companies with advanced AI; https://www.cnbc.com/2023/12/08/75-year-old-tech-mogul-betting-1-billion-of-his-fortune-on-ai-future.html
• Bio of our Chairman Dr. Romesh Wadhwani: Team - SAIGroup (Informal at Romesh Wadhwani - Wikipedia)
• TIME Magazine recently recognized Chairman Romesh Wadhwani as one of the Top 100 AI leaders in the world - Romesh and Sunil Wadhwani: The 100 Most Influential People in AI 2023 | TIME

Opportunity

Get Well is hiring a highly motivated Senior Data Software Engineer to help build and scale our modern cloud-native data platform that supports AI, analytics, and clinical applications. You'll focus on developing robust and compliant data processing workflows while working closely with platform and architecture teams to operationalize next-generation, healthcare-specific data systems.

This role is ideal for an experienced engineer passionate about transforming complex healthcare data into meaningful applications through engineering excellence, collaboration, and innovation. You will play a key role in the continued growth of our data platform and help ensure that our data systems are secure, reliable, and high-performing within the healthcare industry. 

Candidates must have hands-on software development experience with at least one healthcare company—preferably in the provider space—with exposure to EHRs and core healthcare data domains.

Responsibilities

Data Engineering & Pipeline Development

• Design, implement, and maintain scalable batch and real-time data pipelines across a variety of sources and formats.
• Develop high-performance ETL/ELT workflows using tools and frameworks such as Apache Spark, Databricks, dbt, and Snowflake.
• Collaborate with Staff Engineers and Architects to translate platform architecture into executable, maintainable solutions.
• Automate data orchestrations using Airflow or other workflow managers to enable continuous data processing and delivery.

Healthcare Data Integration & Compliance

• Ingest and normalize healthcare datasets (e.g., EHR, FHIR, HL7, CCDA, Claims) in accordance with internal data models.
• Work with governance and compliance teams to meet regulatory requirements including HIPAA and GDPR.
• Implement best practices for encryption, data masking, access control, and auditability across the platform.
• Support efforts around metadata management, data lineage, and structured logging for traceability and transparency.

Platform Optimization & Technical Execution

• Tune Spark-based pipelines and SQL transformations for performance, reliability, and resource efficiency.
• Participate in code reviews, unit testing, and CI/CD processes to ensure code quality and maintainability.
• Work collaboratively across product, informatics, and DevOps teams to translate business needs into technical solutions.
• Contribute to documentation, analytics enablement, and reusability of shared platform components.

Growth, Mentorship & Best Practices

• Mentor junior engineers through code reviews, paired programming, and collaborative development practices.
• Model and advocate for engineering best practices, including clean architecture, effective testing, and proactive monitoring.
• Stay current with trends in distributed systems, cloud-native computing, data privacy, and healthcare interoperability.
• Propose and implement technical upgrades and innovative approaches based on tools like Delta Lake, Apache Iceberg, and emerging GenAI capabilities.

Qualifications

Education & Experience

• Bachelor’s or Master’s degree in Computer Science, Engineering, or related technical field.
• 6+ years of relevant experience in data engineering roles, with at least 3 years focused on cloud-native or large-scale data systems.
• Must have software development experience in at least one healthcare company, preferably in the provider space, with exposure to EHR systems or key healthcare data domains.
• Direct experience designing and building pipelines that move and transform healthcare data, with production-quality data quality checks at scale.

Technical Skills

• Proficient in Python, SQL, and Apache Spark for distributed processing and transformation.
• Hands-on experience with modern data platforms—such as Snowflake, Databricks, Redshift, or BigQuery.
• Deep experience working with public cloud providers, particularly Azure, including native services for data storage, processing, and orchestration (e.g., Azure Data Lake, Azure Synapse).
• Experience with orchestration tools like Airflow and transformation layers such as dbt.
• Familiar with data pipelines in regulated environments, including auditing, encryption, and compliance controls.
• amiliarity with healthcare-specific data formats (FHIR, HL7, EDI) and terminologies (ICD-10, SNOMED, LOINC).

Professional Attributes

• Strong problem-solving skills with a focus on quality, performance, and pragmatism.
• Excellent communication and teamwork skills, with the ability to work across multidisciplinary teams.
• High accountability and ownership mindset with a commitment to excellence in healthcare technology.

About GW RhythmX

GW RhythmX is revolutionizing healthcare through connected, AI-native intelligence that unites clinical insight, patient engagement, and system-wide care orchestration. The company combines market-leading AI precision care technology with extensive trusted patient engagement leadership to help health systems deliver the right care, at the right time, through the right clinician and channel. Its solutions are deployed across more than 150 health systems, touching more than 85M patients including 8M U.S. military veterans. The company's award-winning solutions were recognized again in 2024 by KLAS Research, Fierce Healthcare, and AVIA Marketplace. A SymphonyAI Group company, GW RhythmX leverages various firm assets, including $1B+ in R&D investment, longitudinal data related to 300 million patients, 4.4 billion total annual claims, and 1.8 million healthcare professionals at more than 3,000 facilities globally.

GW RhythmX  is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age or veteran status.

Job Title : Software Engineer III - Data

Location : Bengaluru, IN

About the Role : 

At 6sense, data powers our AI‑first products. We’re looking for a Software Engineer III - Data who builds scalable data pipelines and uses AI tools (prompting + vibe coding) as a daily productivity multiplier.

This is not an ML research role. AI here means using LLMs effectively to build faster and better data systems.

What will you own :

• Write production‑grade code in Java or Python.
• Design and optimize high‑performance SQL on large datasets.
• Work with Spark, Hive, Presto, Kafka, or similar technologies
• Leverage generative AI and AI coding tools to accelerate developer productivity, engineering workflows, and automation of repetitive tasks

AI‑Enabled Engineering (Required)

• Use AI coding tools (Copilot, ChatGPT, Cursor, etc.) for:

1. Writing/refactoring pipeline code
2. SQL generation and optimization
3. Debugging data and performance issues
4. Understanding schemas, logs, and legacy code

• Demonstrate strong prompting skills to guide LLMs effectively.
• Practice vibe coding responsibly—move fast, but validate correctness, performance, and security.

Collaboration & Platform :

• Build data consumed by analytics and AI‑powered product features.
• Partner with Data Science, Backend, and Platform teams.
• Work on AWS‑based data infrastructure (S3, EMR, Redshift, EC2).

What we're looking for :

• 4–7 years of data engineering experience.
• Strong skills in Python and SQL.
• Hands‑on experience with big‑data systems (Spark/Hive/Presto/Kafka).
• Understanding of AI-native software development practices, including automated code generation, AI-driven testing, and human-in-the-loop review systems
• Proven ability to adopt and drive modern engineering paradigms, particularly integrating AI into development workflows to improve productivity, quality, and delivery speed

Nice to Have :

• NoSQL / MPP databases
• Docker / Kubernetes
• Experience supporting AI‑ or LLM‑powered features

One Line Summary on Skills :

• Python + SQL + Spark/Hive/Presto/Kafka + AWS + AI coding tools (prompting & vibe coding).

The Community You Will Join:

The Payments team at Airbnb is crucial to the company's operations, handling critical data related to compliance with Tax, Payments, and Legal regulations. We also manage application data for tools such as CRM, Jira, and Workday, which are essential for Airbnb’s business. Joining this team means working with cross-functional stakeholders, designing scalable solutions, and contributing to a world-class data engineering environment with an emphasis on quality, scalability, and robust engineering practices.

The Difference You Will Make:

Our team charter is on enabling Airbnb to comply with Tax, Payments,and Legal regulations so that our Hosts can continue to operate in regulated geos. Our products ingest, process, validate, and deliver large datasets to government authorities (often partnered with tax remittance) so our data must be of the highest accuracy and quality. As you build and maintain key components of the critical Compliance data ecosystem, you’ll have the opportunity to contribute to creating standards and best practices for Airbnb’s DataEngineering. Your work on solving complex business challenges at scale will be instrumental in shaping the tools, processes, and standards used by the broader data community.

A Typical Day:

• Design, build, and maintain robust and efficient data pipelines that collect, process, and store data from various sources, including user interactions, listing details, and external data feeds.
• Develop data models that enable the efficient analysis and manipulation of data for merchandising optimization. Ensure data quality, consistency, and accuracy.
• Develop high quality data assets for product use-cases by partnering with Product, AI/ML and Data Science.
• Build scalable data pipelines (SparkSQL & Scala) leveraging Airflow scheduler/executor framework
• Collaborate with cross-functional teams, including Data Scientists, Product Managers, and Software Engineers, to define data requirements, and deliver data solutions that drive merchandising and sales improvements.
• Contribute to the broader Data Engineering community at Airbnb to influence tooling and standards to improve culture and productivity
• Improve code and data quality by leveraging and contributing to internal tools to automatically detect and mitigate issues

Your Expertise:

• 6+ years of relevant industry experience
• BE/B.tech in computer science or relevant technical degree
• Hands on experience in DSA coding -Data structure and algorithm
• Extensive experience designing, building, and operating robust distributed data platforms (e.g., Spark, Kafka, Flink, HBase) and handling data at the petabyte scale.
• Strong knowledge of Scala, or Python, and expertise with data processing technologies and query authoring (SQL).
• Demonstrated ability to analyze large data sets to identify gaps and inconsistencies, provide data insights, and advance effective product solutions
• Expertise with ETL schedulers such as Apache Airflow, Luigi, Oozie, AWS Glue or similar frameworks
• Solid understanding of data warehousing concepts and hands-on experience with relational databases (e.g., PostgreSQL, MySQL) and columnar databases (e.g., Redshift, BigQuery, HBase, ClickHouse)
• Excellent written and verbal communication skills

Our Commitment To Inclusion & Belonging:

Airbnb is committed to working with the broadest talent pool possible. We believe diverse ideas foster innovation and engagement, and allow us to attract creatively-led people, and to develop the best products, services and solutions. All qualified individuals are encouraged to apply.

As a Senior Data Engineer, you will design, build, and manage components of our highly available real-time and batch data pipelines handling petabytes of data. Our pipeline platform is designed to ingest and process billions of events per day, and make the resulting aggregations and insights available within minutes in our analytical data stores. Data Analytics is at the core of our business, and we’re constantly innovating to make our systems more performant, timely, cost-effective, and capable while maintaining high reliability. You will build on top of our core data infrastructure and pipelines using technologies and tools tailored for massive data sets including Flink, Spark, Kafka, Iceberg and Druid while working in the AWS cloud environment.  

If you are interested in building systems that can consume and explore billions of data points a day, work with petabytes of data, and want to push what is possible with data, this is the place for you!

As a Senior Data Engineer, you’ll get to:

• Architect, build, and own real-time and batch data aggregation systems to deliver quality analytical reports for our internal and external customers.
• Collaborate with Data Scientists, Backend Engineers, Data & Infrastructure Operations, and Products Managers to deliver new features and capabilities for customers.
• Develop clean, safe, testable, and cost-efficient solutions.
• Make well-informed decisions with deep knowledge of both the internal and external impacts on teams and projects. Foresee shortcomings ahead of time and be able to drive to resolution.

You’ll be a good fit if you have:

• Bachelors in CS or equivalent.
• 6+ years of Software Engineering or Data Engineering experience with a recent focus on big data. 
• Strong development skills in Java or Scala and Python.
• Solid background in the fundamentals of computer science, distributed systems, large scale data processing as well as database schema design and data warehousing.
• Practical experience managing AWS or Google Cloud environments.
• Experience in containerized deployment or Kubernetes is a big plus!
• Good understanding of a broad spectrum of NoSQL, traditional RDBMS, and analytical/columnar data stores including Postgres, Druid, Vertica, Redshift, Hadoop, Hive, Cassandra, Aerospike, and Redis.
• Ability to build systems that balance scalability, availability, and latency.
• Strong ability to advocate for the continual deployment and automation tools, monitoring, and self-healing systems that can help improve the lives of our engineers.
• Great communication skills and you are a team player who has a proven track record of building strong relationships with management, co-workers, and customers.
• A desire to learn and grow, push yourself and your team, share lessons with others and provide constructive and continuous feedback, and be receptive to feedback from.

This role will be based at our Bengaluru, KA office and follows a Hybrid schedule that will be aligned with our Return to Office guidelines. 

The Community You Will Join:

The BizTech team at Airbnb is crucial to the company's operations, handling critical data related to compliance with Tax, Payments, and Legal regulations. We also manage application data for tools such as CRM, Jira, and Workday, which are essential for Airbnb’s business. Joining this team means working with cross-functional stakeholders, designing scalable solutions, and contributing to a world-class data engineering environment with an emphasis on quality, scalability, and robust engineering practices.

The Difference You Will Make:

We are looking for a hands-on expert to provide technical leadership in addressing BizTech’s diverse data engineering needs and driving long-term strategies and best practices. This key leadership role requires strong collaboration and influence across teams. You'll play a crucial role in understanding business needs, identifying the right data sources, designing efficient data models, and building reliable, scalable data pipelines. As technology continues to evolve, you'll help shape and maintain significant parts of BizTech’s critical data ecosystem. Your contributions will not only address complex business challenges but also help refine and advance Airbnb’s Data Engineering Paved Path, benefiting the entire data community at Airbnb. We believe in solving problems and contributing back to our data community to continuously improve.

A Typical Day /Responsibilities:

• Lead the design, implementation, and testing of data systems, from architecture to production.
• Build batch and real-time data systems that support business needs and critical products.
• Ensure data systems' quality, performance, and stability through rigorous monitoring and quality assurance practices.
• Design and optimize data models to efficiently meet business and product requirements.
• Collaborate with cross-functional teams, including product managers, data scientists, and engineers, to develop scalable systems and drive data-driven decisions.
• Maintain strong partnerships with backend, data science, and machine learning teams to ensure seamless integration of data systems.
• Contribute to long-term data strategies and influence data engineering practices across the organization.
• Mentor and guide team members, fostering best practices for data quality and governance.
• Advance 3rd party data integrations, enhancing frameworks for data exchange, governance, and lineage.

Your Expertise:

• 9+ years of relevant experience with a Bachelor's/Master’s degree in CS/EE (or 6+ years with a PhD).
• Extensive experience in designing, building, and operating distributed data platforms (e.g., Spark, Kafka, Flink) at a large scale.
• Proficiency in Java, Scala, or Python, along with strong skills in data processing and SQL querying.
• Proven track record of designing and optimizing batch and real-time data pipelines.
• Strong collaboration skills with the ability to work with product managers, data scientists, and engineers.
• Advanced problem-solving and analytical skills, with a focus on data quality, governance, and system reliability.
• Excellent written and verbal communication, with the ability to influence stakeholders and convey complex technical concepts.
• Expertise in data modeling, warehousing, and working with relational and columnar databases (e.g., PostgreSQL, MySQL, Redshift, BigQuery).
• Experience with integrating machine learning models into data systems (preferred).
• Strong leadership and mentorship capabilities, with experience guiding teams on best practices and technical strategies.
• Flexible and innovative, with the ability to adopt new technologies to enhance data systems and processes.

About Us

OpenFX is on a mission to move money as freely as data, unrestricted by time zones, banking hours, or legacy systems. We are building the infrastructure that will power the next generation of cross-border payment systems for institutions. The team's execution has been exceptional, and we're scaling at a remarkable pace. Our stellar early team comes with experience in companies like J.P. Morgan, Goldman Sachs, FalconX, Paypal, Affirm, Polygon, Kraken, Nium & others. We're backed by Accel, Faction, NfX, Accomplice, and other top-tier investors.

Role Overview

OpenFX processes billions of dollars in transaction volume across global corridors. Every decision around pricing, risk, liquidity, reconciliation, and compliance depends on accurate, timely, and trustworthy data. We need Data Engineers who can build reliable data pipelines, ensure data correctness end to end, and make data usable for analytics, risk, and operations at scale. You will own critical data infrastructure that directly powers our financial operations.

Key Responsibilities

• Own 1 to 2 critical data pipelines that ingest, transform, and publish production data
• Design data models that are accurate, auditable, and easy to consume
• Build reliable ingestion pipelines from transactional systems and external partners
• Ensure data correctness and freshness through validation, monitoring, and backfills
• Handle late-arriving, duplicate, and inconsistent data safely
• Partner with Backend, Analytics, Risk, and Ops teams to translate requirements into robust data solutions
• Improve core data metrics such as pipeline reliability, data latency, and reconciliation accuracy
• Automate pipeline operations including retries, recovery, and backfills

What We're Looking For

Required

• 3 to 7 years experience in data engineering or backend data systems
• Strong SQL and data modeling fundamentals
• Experience building batch and/or streaming pipelines
• Experience working with relational databases and data warehouses
• Experience handling schema evolution and backfills
• Understanding of data quality, validation, and monitoring
• Ability to clearly explain data tradeoffs

Preferred

• Experience with Kafka, Spark, or Flink
• Experience with modern warehouses (BigQuery, Snowflake, Redshift)
• Experience with Airflow or similar orchestration tools
• Experience in fintech or regulated domains
• Familiarity with event-driven architectures
• Experience mentoring junior engineers

What We Offer

• Competitive salary and benefits package.
• Equity in a rapidly growing company.
• Opportunity to work in a fast-paced startup at the forefront of fintech innovation.
• Opportunity to make a significant impact on global financial infrastructure.
• Collaborative work culture with emphasis on personal and professional growth.

We are committed to building a diverse and inclusive workplace. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or veteran status.

We are growing our data science team and looking for a passionate individual who can bridge the gap between business problems and data solutions.

Key Responsibilities

• Own the end-to-end problem-solving lifecycle: business context → data → AI-driven insights → outcomes
• Work directly with customers and internal teams to understand business problems and define solutions
• Analyze large, complex datasets using SQL and Python
  
• Design and deliver AI-powered analytics solutions using Tellius
• Translate ambiguous business problems into structured analytics or AI workflows
  
• Build and demo insight-driven dashboards and narratives for business users
• Partner closely with Product, Engineering, and GTM teams
  
• Present insights and recommendations confidently to business and technical stakeholders
  

Must-Have Skills

• 3+ years of experience in data science, solutions engineering, or analytics consulting
• Strong hands-on skills in SQL and Python
  
• Experience with cloud data platforms (Snowflake, Databricks, Redshift)
• Hands-on experience with LLMs and AI agents, including prompt engineering, RAG pipelines, AI agent workflows, and deploying AI-driven solutions beyond basic ChatGPT usage.
• Understanding of agentic AI concepts: memory, tool usage, orchestration, multi-step reasoning
• Experience with analytics platforms such as Tableau, Power BI, and ThoughtSpot (you understand what Tellius replaces)
• Domain exposure in pharma commercial analytics, CPG/retail analytics, or FP&A (at least one)
• Strong storytelling, presentation, and stakeholder management skills
• Comfortable in customer-facing roles
  

Good to Have

• Prior experience in an analytics or AI SaaS product company
  
• Exposure to enterprise decision workflows
  
• Experience demoing or solutioning for clients

Who You Are

• Curious, analytical, and business-minded
• Comfortable working in ambiguity
• Excited about AI-native analytics and agentic systems
  
• Strong communicator who can turn insights into action

Why Join Tellius

• Build next-gen, AI-native analytics products
  
• Work on real customer problems with measurable impact
• Collaborate with top talent across AI, data, and product
• Fast growth, high ownership, and strong learning opportunities

What You Will Do and Learn

As a Data Engineer in Data Solutions, you’ll be responsible for designing, implementing, and testing proposed modern analytic solutions.  Working closely with our client partners and architects, you’ll develop relationships with key technical resources while delivering tangible business outcomes. 

Qualifications:

· 2-4 years’ experience developing industry leading business intelligence and analytic solutions

· Must have thorough knowledge of data warehouse concepts and dimensional modelling

· Must have experience in writing advanced SQL

· Must have at least 2+ years of hands-on experience on DBT (Data Build Tool). Mandatory to have most recent hands-on experience on DBT.

· Must have experience working with DBT on one or more of the modern databases like Snowflake / Amazon Redshift / BigQuery / Databricks / etc.

· Hands-on experience with Snowflake would carry higher weightage

· Snowflake SnowPro Core certification would carry higher weightage

· Experience working in AWS, Azure, GCP or similar cloud data platform would be an added advantage

· Hands-on experience on Azure would carry higher weightage

· Must have experience in setting up DBT projects

· Must have experience in understanding / creating / modifying & optimizing YML files within DBT

· Must have experience in implementing and managing data models using DBT, ensuring efficient and scalable data transformations

· Must have experience with various materialization techniques within DBT

· Must have experience in writing & executing DBT Test cases

· Must have experience in setting up DBT environments

· Must have experience in setting up DBT Jobs

· Must have experience with writing DBT Jinja and Macros

· Must have experience in creating DBT Snapshots

· Must have experience in creating & managing incremental models using DBT

· Must have experience with DBT Docs

· Should have a good understanding of DBT Seeds

· Must have experience with DBT Deployment

· Must Experience with architecting data pipelines using DBT, utilizing advanced DBT features

· Proficiency in version control systems and CI/CD

· Must have hands-on experience configuring DBT with one or more version control systems like Azure DevOps / Github / Gitlab / etc.

· Must have experience in PR approval workflow

· Participate in code reviews and best practices for SQL and DBT development

· Experience working with visualization tools such as Tableau, PowerBI, Looker and other similar analytic tools would be an added advantage

· 2+ years of Business Data Analyst experience

· 2+ years of experience writing Business requirements, Use cases and/or user stories, for data warehouse or data mart initiatives.

· Understanding and experience on ETL/ELT is an added advantage

· 2+ years of consulting experience working on project-based delivery using Software Development Life Cycle (SDLC)

· 2+ years of years of experience with relational databases (Postgres, MySQL, SQL Server, Oracle, Teradata etc.)

· 2+ years of experience creating functional test cases and supporting user acceptance testing

· 2+ years of experience in Agile/Kanban/DevOps Delivery

· Outstanding analytical, communication, and interpersonal skills

· Ability to manage projects and teams against planned work

· Responsible for managing the day-to-day client relationship on projects

· Manage the Data engineering lifecycle including research, proof of concepts, architecture, design, development, test, deployment, and maintenance

· Collaborate with team members to design and implement technology that aligns with client business objectives

· Build proof of concepts for a modern analytics stack supporting a variety of Cloud-based Business Systems for potential clients

· Team management experience and ability to manage, mentor and develop talent of assigned junior resources

· Create actionable recommendations based on identified platform, structural and/or logic problems

· Communicate and demonstrate a clear understanding of client business needs, goals, and objectives

· Collaborate with other architects on solution designs and recommendations.