This position does not offer visa sponsorship now or in the future.

We’re looking for an Analytics & Business Intelligence, AVP to measurably drive growth for our Operations and Investment Management (OIPM) group at iCapital.

This role involves defining and calculating operational KPIs, transforming raw source data into processed business data, creating live dashboards to monitor performance, identifying driver metrics and statistical correlations, and finally working with business teams to enable data-driven change.

You will sit in the Analytics group of the broader Data & Analytics team within Technology, and will work closely with our Data Engineering group. Although you are initially expected to be an individual contributor, the role would eventually entail managing a team of 1-3 direct reports.

On the technical side, you will interface with our data stack of Airbyte, Snowflake, dbt, Prefect, Python and Tableau (among others). On the business side, you will work with our operations teams to produce management visibility, efficiency improvements and workflow automation.

Ideal candidates will be highly proficient in our technical tooling, understand complex business problems, interface with senior stakeholders, develop execution plans, and finally present on their work.

Responsibilities:

• Write SQL within dbt to extract, transform, validate, and aggregate data.
• SQL / DBT - 50%; Tableau/PowerBI - 30%; Python - 20%
• Create Tableau dashboards for various business teams, charting key metrics and performing exploratory data analysis
• Monitor and deploy data pipelines into our orchestration infrastructure using Prefect
• Drive projects to completion by gathering business requirements, implementing technical solutions, following software best engineering practices, and finally presenting on results
• Work closely with our engineering, product and business teams to form a thorough understanding of our industry and evolving data model
• Convert data insights into concrete, action-oriented and phased execution plans that measurably grow various business metrics over time

Required Qualifications:

• Bachelor’s degree or higher in Computer Science, Economics, Mathematics, Statistics or a related technical field
• 4 to 8 years of experience in a data-related role
• Excellent writing, communication and presentation skills
• Excellent knowledge of SQL (dbt experienced preferred)
• Good knowledge of a business intelligence tool (e.g. Tableau, Looker, PowerBI)
• Good knowledge of Python, Microsoft Excel and intermediate statistics
• Familiar with data science techniques and machine learning models
• Prior experience with end-to-end project delivery (e.g. requirements gathering, scoping, working within large organizations, presenting on project plans and results)
• Detail-oriented, naturally curious and willing to question to status quo to understand business needs

Preferred Qualifications:

• Prior experience in the financial services and alternative investments
• Prior experience in business analyst and/or project management roles

Benefits

The base salary range for this role is $100,000 to $135,000 depending on level and experience.  iCapital offers a compensation package which includes salary, equity for all full-time employees, and an annual performance bonus. Employees also receive a comprehensive benefits package that includes an employer matched retirement plan, generously subsidized healthcare with 100% employer paid dental, vision, telemedicine, and virtual mental health counseling, parental leave, and unlimited paid time off (PTO).

We believe the best ideas and innovation happen when we are together. Employees in this role will work in the office Monday-Thursday, with the flexibility to work remotely on Friday.

For additional information on iCapital, please visit https://www.icapitalnetwork.com/about-us  Twitter: @icapitalnetwork | LinkedIn: https://www.linkedin.com/company/icapital-network-inc | Awards Disclaimer: https://www.icapitalnetwork.com/about-us/recognition/

iCapital is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, gender, sexual orientation, gender identity, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics.

This position does not offer visa sponsorship now or in the future.

iCapital is seeking an exceptional Data Engineer to help scale the data foundations that power the business. This individual will design, build, and optimize the data pipelines and infrastructure that enable data to be a strategic asset across the organization. This role is highly collaborative and will partner with the Product, Engineering, Analytics teams and business stakeholders to quickly understand evolving challenges and deliver scalable, maintainable, and high‑quality solutions.

Data sits at the core of iCapital’s operations. The firm relies on clean, reliable, well‑structured data to drive decision‑making, enhance client experiences, and support a rapidly growing product suite. This individual will be responsible for moving and transforming data and developing a deep understanding of the business context behind it and help teams act on insights.

Responsibilities

• Develop and automate large scale, high-performance data platform pipelines and infrastructure to drive iCapital business growth and enable data-driven decision making.
• Design and develop reusable components and frameworks for ingestion, cleansing, and data quality.
• Streamline the ingestion of raw data from various sources into our Data Lake and Data Warehouse.
• Design data models for optimal storage and retrieval that represent the tangible business domains across iCapital’s ecosystem.
• Coordinate closely with the Operations, Sales, and Product Development teams daily to push iCapital’s FinTech strategy and improve the overall profitability of the business.

Qualifications

• 6-10 years of professional experience in a data engineering or data-driven software engineering role
• Exceptional Python and SQL skills
• Extensive experience with orchestration frameworks (Prefect, Airflow, Dagster, etc.)
• Deep understanding of OLAP (Snowflake, Databricks) and OLTP (PostgreSQL, MongoDB) databases and ELT frameworks (dbt, dlthub)
• Experience developing and deploying code to Cloud environments (AWS, GCP, Azure)
• Possess a strong grasp of object-oriented and functional programming and an ability to write easy-to-scale, high-quality code
• Experience leveraging stream processing frameworks (Kafka, Flink, Spark)
• Knowledge of infrastructure-as-code frameworks (terraform or cloud formation)
• Detail-oriented and able to multitask and work in a fast-paced environment
• Able to work independently while also being a strong team player
• Excellent written and verbal communication
• Passionate about learning and mastering cutting-edge technologies
• Professional experience with JVM based languages such as Scala, Java, and Kotlin is preferred
• Knowledge of financial markets and financial instruments is preferred

Benefits

The base salary range for this role is $100,000 to $135,000.  iCapital offers a compensation package which includes salary, equity for all full-time employees, and an annual performance bonus. Employees also receive a comprehensive benefits package that includes an employer matched retirement plan, generously subsidized healthcare with 100% employer paid dental, vision, telemedicine, and virtual mental health counseling, parental leave, and unlimited paid time off (PTO).

We believe the best ideas and innovation happen when we are together. Employees in this role will work in the office Monday-Thursday, with the flexibility to work remotely on Friday.

For additional information on iCapital, please visit https://www.icapitalnetwork.com/about-us  Twitter: @icapitalnetwork | LinkedIn: https://www.linkedin.com/company/icapital-network-inc | Awards Disclaimer: https://www.icapitalnetwork.com/about-us/recognition/

iCapital is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, gender, sexual orientation, gender identity, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics.

The Role

Analytics Engineering at Flex sits at the intersection of Data, Product, Engineering, and business objectives. As Director, Analytics Engineering you will run the team that enables stakeholders at Flex to easily find the data they need to make decisions. You’ll be responsible for developing a world-class analytics platform that powers all data consumption at Flex, as well as managing and developing a team of high-performing Analytics Engineers. You'll also be hands-on, leveraging your technical skills to develop data models and build better data products and solutions. You'll partner with analysts, engineers, PMs and others to define the requirements while being accountable for delivering the end data product.

You Will:

• Develop and lead strategy for data modeling platform and team roadmap
• Manage and mentor a team of Analytics Engineers
• Collaborate with leaders across product & engineering teams to define data requirements and inform architecture/schema design decisions
• Lead the development of data models to consume, transform, and expose data to stakeholders and systems across the company
• Collect business requirements, define successful analytics outcomes, and design data solutions
• Set company-wide standards for data regarding structure, quality, and expectations
• Contribute Flex’s data culture by influencing processes, systems, and tools that enable to make better decisions in a scalable way

You Have:

• 8+ years as an analytics engineer or equivalent, with a track record of shipping high quality products and features at scale
• Expert knowledge of SQL, data warehouses (we use Snowflake), and how to write efficient SQL queries
• Familiarity with common BI tools (preferably Sigma Computing, Tableau, Mode, etc.)
• Expert proficiency with dbt, dbt Cloud, and Airflow
• Strong perspective on analytics engineering development cycle (data modeling, version control, documentation + testing, and best practices for codebase development and CI/CD)
• Proficiency with Python preferred
• Experience within the fintech space preferred

Flex takes a market-based approach to pay, and compensation may vary depending on your primary work location. Work locations are categorized into one of three tiers based on a cost of labor index for that geographic area.  

Tier A (NYC/SF/Seattle): $240,000-290,000
Tier B (Austin, Washington D.C. Philadelphia, Los Angeles, San Diego, Chicago, Miami, Atlanta : $215,000-265,000
Tier C (SLC/All Other States): $200,000-250,000

Offices

Roles posted in New York, San Francisco, or Salt Lake City are hybrid positions with on-site expectations of 2-3 days per week in our local offices. For candidates outside of these areas, you may be eligible for our relocation assistance program.

About the role

We are seeking a highly skilled Senior BI Engineer to take ownership of our Snowflake data platform and help evolve it into a scalable, well-governed foundation for analytics and AI. This is a hands-on engineering role responsible for shaping data architecture, enforcing standards, and building a clean, reliable data layer that supports both business intelligence and AI-driven use cases. You will report directly to the Director of BI and have significant autonomy in how the platform evolves. 

What You’ll Do 

Own and Elevate the Data Platform 

• Own the design and evolution of our Snowflake data platform end-to-end 
• Refactor and enhance pipelines, dbt models, and transformations to meet high standards for scalability, performance, and maintainability 
• Make and drive architectural decisions—not just implement tasks 

Architect for Scale and Clarity 

• Implement and enforce medallion architecture (bronze/silver/gold) with clear separation of concerns 
• Design and build dimensional models (star schemas) that are intuitive, performant, and durable 
• Implement SCD Type 2 and other core warehousing patterns correctly and consistently 
• Establish and enforce standards for schemas, naming, and data contracts 
• Integrate and normalize data from a wide range of source systems (SaaS apps, operational databases, event streams, finance/CRM tools) into a coherent, well-modeled warehouse layer 

Build an AI-Ready Data Layer 

• Design data models optimized for semantic clarity and AI/LLM consumption 
• Implement semantic views in Snowflake to enable tools like Claude via MCP 
• Ensure data is traceable, explainable, and trustworthy 

Establish a Real Data Engineering SDLC 

• Implement a Git-driven development lifecycle (branching, PR reviews, testing, deployments) 
• Introduce and enforce: 
• Data quality testing and validation 
• Schema enforcement and regression safeguards 
• Clear promotion paths from dev → prod 
• Raise the bar on engineering discipline across the data function 

Leverage AI as a Force Multiplier 

• Use AI tools to accelerate development while maintaining high standards 
• Guide and validate AI-generated code—never blindly trust it 
• Explore agent-based approaches for: 
• Data quality auditing 
• Pipeline validation 
• Anomaly detection and monitoring 

Collaborate and Lead Technically 

• Partner with BI analysts to deliver reliable, well-modeled datasets (Power BI downstream) 
• Translate ambiguous business requirements into clean, scalable data models 
• Provide technical direction to a supporting QA/offshore resource (planned) 

Documentation & Transparency 

• Build a culture of clear documentation, lineage, and data discoverability 
• Ensure systems are understandable and maintainable by others 
• Other duties as assigned 

What You’ll Need to be Successful 

Data Engineering Depth & Ownership 

• 5+ years of hands-on data engineering experience, with a meaningful portion spent owning architecture and driving development — not just executing assigned tasks 
• Strong experience with Snowflake as a primary warehouse 
• Advanced SQL skills and experience building production-grade ELT pipelines 
• Strong hands-on experience with dbt for modeling, testing, and transformation — including macros, tests, snapshots, and managing a production dbt project at scale 
• Experience integrating and normalizing data from many disparate source systems — SaaS APIs, application databases, CRM/ERP, finance systems, event data — into consistent, analytics-ready models 
• Deep, hands-on experience with: 
  • Star schemas and dimensional modeling 
  • SCD Type 2 implementations 
  • Layered/medallion architectures 
• Ability to make tradeoffs and defend decisions (performance vs flexibility, normalization vs usability, etc.) 
• Track record of improving data quality, consistency, and trust 
• Experience implementing Git-based workflows and structured SDLC practices for data 
• Strong instincts around testing, governance, and maintainability 
• Comfortable setting and enforcing standards across a team 

AI-First Mindset

• Demonstrated ability to use AI tools to meaningfully increase output and velocity 
• Strong judgment to validate and refine AI-generated work 
• Interest in applying AI/agents to improve data engineering workflows 

What Will Make You Stand Out

• Familiarity with Power BI 
• Familiarity with Salesforce as a data source (objects, schema, Salesforce-to-warehouse pipelines) 
• Experience working with or leading offshore/support resources

What You’ll Love About NetDocuments 

• The People! 
• 90% healthcare premiums company covered 
• HSA company contribution 
• 401K match at 4% with immediate vesting 
• Flexible PTO (typically 3 to 4 weeks a year) 
• 10 paid holidays 
• Monthly contributions for life activities & wellness 
• Access to LinkedIn learning with monthly dedicated time to explore 

Compensation Transparency 

The compensation range for this position is:  $155,000-$165,000

The posted cash compensation for this position includes on target earnings, base salary and variable if applicable. Some roles may qualify for overtime pay. Individual compensation packages are determined based on various factors specific to each candidate, such as career level, skills, experience, geographic location, qualifications, and other job-related

#LI-HYBRID

We Are Route

When shoppers hit "buy," a great customer experience doesn’t end, it’s just getting started. For too long, everything after checkout has been the weakest link in ecommerce: confusing tracking, lost or damaged packages, clunky returns, and missed opportunities to turn first-time buyers into lifelong fans. That's why we built Route.

Our mission is simple: we create shopper confidence that fuels brand growth. Route is the leading post-purchase platform for modern ecommerce, trusted by thousands of brands and protecting more than $20 billion in gross merchandise value to date. From package protection and industry-leading order tracking to returns and exchanges, cash back loyalty, and engaging product recommendations, Route brings every moment after checkout into one powerful platform, empowering shoppers with visibility and peace of mind while giving merchants loyalty that lasts well beyond the first sale.

Since launching in 2018, Route has raised over $250 million from leading investors including Craft Ventures, Hedosophia, and Hanaco Ventures, and has grown into a complete post-purchase ecosystem loved by millions of shoppers and the brands they buy from. Throughout that growth, we've stayed committed to building innovative products that empower our customers and to fostering a people-first, values-driven culture that makes Route a place where great work and great people thrive.

We're looking for talented people across the ecommerce space to join us on the next chapter of this adventure. Don't just take our word for it, Discover what life at Route has to offer.

The team

The Data Engineering team (DAENGR) is the backbone of Route's data ecosystem. We are primarily responsible for the data infrastructure, quality, standards, frameworks, and architecture that power enterprise data, reporting, and analytics across the entire organization. We solve problems of poor data quality and limited accessibility, simplify reporting for teams outside of data engineering, and monitor the uptime, security, and consistency of the majority of Route's data lifecycle. We collaborate closely with every corner of the business to make data a first-class citizen at Route.

The opportunity

This is a rare chance to shape the data destiny of a young, fast-growing company at an inflection point. As Route moves into the AI era of data infrastructure, you'll have the opportunity to leave a lasting legacy — exploring new systems and designs, and building tools that genuinely change how Route operates day to day. We are actively migrating from legacy Snowflake pipelines into a modern Databricks-first architecture, building out an Enterprise Data Warehouse (EDW) with a normalized 3NF core, and laying the groundwork for AI-ready data systems. You'll be co-authoring the next chapter of data at Route.

The ideal candidate is organized and articulate in their thinking, able to adapt and compromise to keep pace with business needs, but firm enough to push back when security and data integrity are at stake. We aim to help Route improve profitability, cash flow, and return on investment by providing accurate data to make informed decisions and process improvements.

What you’ll do

• Build and maintain ELT pipelines that ingest data from systems.
• Co-own the mapping and migration of source data into the new 3NF EDW, ensuring data integrity, reducing redundancy, and maintaining automated unit and data tests.
• Develop data observability processes and monitoring dashboards to track pipeline health, freshness, and data quality across Databricks.
• Build new data and AI-powered tooling to improve the productivity of the data engineering team and broaden self-service data access for Route employees and external partners.
• Help harden the Integration Pipeline by automating deployment of shared staging and production infrastructure for new pipelines and managing dependency updates for dbt and CI templates.
• Support the full migration from Snowflake to Databricks, targeting completion by end of Q2 2027, including reporting services and ingest/egress jobs.
• Coordinate with engineering, analytics, product, and business teams to define and prioritize data requirements and ensure end-to-end data lifecycle coverage for existing and new products.
• Champion data democratization, help establish a company-wide data retention policy, and expand the foundation for a self-service Silver layer (EDW) that serves as a single source of truth.

What we’re looking for

• 5+ years of formal, professional data engineering experience
• 4+ years of SQL, fluency in complex transformations, window functions, query optimization
• 3+ years of python, data pipeline development, scripting, testing, and package management (Poetry)
• 2+ years of experience with AWS (e.g. - S3, RDS, DMS, DynamoDB) across data-related services
• 1+ years of experience using Databricks, our primary development platform for this role
• Experience using Terraform and GoLang
• PagerDuty / Grafana / Tableau, preferred experience
• Understanding of third normal form (3NF) data modeling and when to apply it
• Knowledge and application of data theory
• Working knowledge of data security practices and least-privilege access standards
• Experience with data access controls in cloud environments (IAM roles, catalog permissions, etc.)

Equal opportunity for all

Route is an Equal Opportunity Employer. We embrace diversity and equal opportunity in a serious way. We are committed to building a team that represents a variety of backgrounds, perspectives, and skills. The more inclusive we are, the better our work will be.

Total Rewards

We know our team works best when everyone feels happy, healthy, and supported. We offer to pay 95% - 100% of your health insurance premiums for you and your family, remote or hybrid work arrangements, unlimited PTO, 401k matching, formalized growth opportunities, learning & development, DEI programs & events, and so much more.

Pay Transparency

Salary for this role: $138,000 - $146,000

The cash compensation above includes base salary, and is not reflective of potential commission for employees in eligible roles, or annual bonus targets under Route’s bonus plan for eligible roles. In addition to cash compensation, all Route employees are eligible to participate in Routes equity incentive plan to receive stock options per the terms of the agreement. Some roles may also be eligible for overtime pay. Individual compensation packages are based on a few different factors unique to each candidate, including their career level, skills, experience, specific geographic location qualifications and other job-related reasons.

ABOUT THIS ROLE

As Data Engineer, AI, you will play a key role in building and advancing LVT’s data platform — contributing across the full data engineering lifecycle, from ingestion and transformation to semantic modeling and delivery — while also helping build the data infrastructure that powers LVT’s AI initiatives, including RAG pipelines and Snowflake Cortex models. This is a core engineering role with an AI edge: you’ll keep the data platform running with precision and reliability, and you’ll be the person who makes sure our AI systems have the clean, well-structured data they need to perform.

LVT is a flexible-first company. This role can be performed remotely, with a preference for candidates who can work from our American Fork, UT office.

ROLE RESPONSIBILITIES

• Design, build, and maintain scalable ELT pipelines that move data reliably from source systems into a clean, well-governed data platform.
• Develop and maintain semantic models that expose consistent, trusted business definitions across reporting and analytics surfaces.
• Own data quality — implement validation, monitoring, and alerting frameworks that catch problems before they reach stakeholders.
• Optimize Snowflake performance across ingestion, transformation, and storage, including dynamic tables, clustering, and query tuning.
• Architect and build the data infrastructure required for RAG applications, including vector storage, chunking strategies, and retrieval pipelines.
• Collaborate with AI/ML engineers to support Snowflake Cortex model development with well-structured, context-rich training and inference data.
• Partner with analytics engineers, data scientists, and business stakeholders to translate requirements into durable data solutions.
• Document data architecture, pipeline design, and modeling decisions to support team knowledge and long-term maintainability.

OUR IDEAL CANDIDATE

• Data Engineering Foundation: 5+ years building and maintaining production-grade pipelines using SQL, Python, and modern ELT tools such as dbt, Fivetran, or Airflow.
• Snowflake Proficiency: Deep hands-on experience with Snowflake, including performance optimization, dynamic tables, and familiarity with Cortex AI capabilities.
• Semantic Modeling Experience: Ability to design and maintain semantic or metrics layers that enforce consistent business logic across the organization.
• AI Infrastructure Awareness: Working knowledge of RAG architectures and the data patterns — chunking, embedding, retrieval — that support LLM-driven applications.
• Data Quality Ownership: Strong instinct for reliability — you instrument pipelines with observability and validation from the start.
• End-to-End Mindset: Comfortable owning work from scoping through production — you define the problem, build the solution, and stand behind the outcome.
• Collaborative Communicator: Able to work fluidly with engineers, analysts, and non-technical stakeholders, translating ambiguity into clear data solutions.

About the Role

We’re looking for a Senior Data Engineer to design, build, and optimize our data platforms so teams across the company can make fast, reliable, data-driven decisions. You’ll be a key technical leader, owning end-to-end data pipelines and modeling, and setting best practices around how we work with data.

You’ll work heavily with Databricks, Spark, SQL, and Python, building scalable data solutions that power analytics, reporting, and data products. Experience in payments or financial services is a strong plus.

What You’ll Do

• Design and build data pipelines
• Develop, maintain, and optimize ETL/ELT pipelines on Databricks and Spark.
• Integrate data from multiple internal and external sources into a centralized data platform.
• Own data modeling & architecture
• Design and maintain robust data models (e.g., star/snowflake schemas, data vault, dimensional models) to support analytics and self-service BI.
• Establish and enforce data modeling standards and documentation.
• Ensure data quality, reliability, and performance
• Implement data quality checks, validation frameworks, and monitoring.
• Tune queries and jobs for performance and cost efficiency in Databricks and downstream systems.
• Collaborate and lead
• Partner with data analysts, data scientists, and product/engineering teams to understand data needs and translate them into technical solutions.
• Provide technical leadership and mentorship to other data engineers; help review designs and code.
• Governance & best practices
• Contribute to and refine our data governance, security, and access control practices.
• Drive best practices around version control, CI/CD for data, and code standards.

Required Qualifications

• 7+ years of professional experience as a Data Engineer, Software Engineer, or similar role.
• Strong hands-on experience with Databricks (or a very similar cloud data platform) including cluster management, jobs, and notebooks.
• Advanced experience with Apache Spark for batch and/or streaming data processing.
• Expert-level SQL skills (complex joins, window functions, query optimization).
• Strong Python skills for data engineering (e.g., PySpark, data processing libraries, scripting).
• Proven experience in data modeling and designing schemas for analytics and reporting.
• Experience building and maintaining data pipelines in a cloud environment (AWS, Azure, or GCP).
• Strong understanding of data warehousing concepts, ETL/ELT best practices, and data lifecycle.
• Solid software engineering fundamentals: version control (git), testing, code reviews, and CI/CD.
• Excellent communication skills and the ability to collaborate with technical and non-technical stakeholders.

Nice to Have

• Experience in payments, fintech, banking, or broader financial services (e.g., transaction data, ledgers, risk, fraud, reconciliation).
• Experience with streaming technologies (e.g., Spark Structured Streaming, Kafka, Kinesis, or similar).
• Familiarity with dbt or similar transformations-as-code frameworks.
• Experience with orchestration tools (e.g., Airflow, Databricks Workflows).
• Knowledge of BI tools (e.g., Power BI, Tableau, Looker) and how data models power them.
• Exposure to machine learning workflows and supporting data science teams.
• Experience implementing data governance, lineage, and catalog tools.

What You’ll Bring

• A product mindset: you think about the end users of data and build with usability in mind.
• A bias for automation, reliability, and scalability over one-off solutions.
• Comfort with ambiguity, ownership of complex problems, and a desire to continuously improve the data ecosystem.

What We Offer

• 401k investment opportunity, with company match   
• Medical, Dental, and Vision Plans
• Paid Time Off   
• Paid Parental Leave
• Paid Volunteer Leave

Role Information: 

• Full-Time, On-site, Provo

ABOUT THIS ROLE 

As the Sr. Manager of Data Engineering and Architecture, you will be a hands-on leader responsible for defining and executing the data engineering strategy, architecture, and technology stack. You will be responsible for the foundational data infrastructure that powers analytics and decision-making across the organization.

A critical part of this role will be building, mentoring, and managing a team of 3 data engineers. You will guide the team's efforts while also contributing directly to the development of our modern data warehouse in Snowflake using dbt and SQL, transforming raw data into reliable and accessible datasets. Crucially, you will spearhead the data migration efforts for our ongoing Oracle Fusion Cloud deployment, designing a robust, cohesive data ecosystem that bridges our new Oracle environment with Snowflake.

Your leadership will ensure the successful design, build, and maintenance of robust data pipelines that ingest data from a variety of internal and external sources into Snowflake. Your team's work will support reporting, dashboarding, and analysis across the company, enabling teams to make informed decisions based on trusted data. Given the green-field nature of this initiative, the role is expected to be approximately 30% technical leadership, strategy, and people management, and 70% direct, hands-on engineering and architecture.

This position is based in a hybrid work environment and requires regular in-office collaboration. It offers an opportunity to lead with modern data tools, build a high-performing team, and make a direct, strategic impact on data quality and accessibility during a massive phase of enterprise scaling.

ROLE RESPONSIBILITIES

• Data Strategy & Architecture: Define the long-term vision, strategy, and architecture for the company’s data platform. Design a cohesive hybrid architecture that maximizes the strengths of our full tech stack, ensuring it drives measurable business value and scales efficiently to support hyper-growth.

• Team Leadership & Management: Build, mentor, and manage a team of 3 data engineers, fostering a culture of technical excellence, accountability, and continuous improvement.

• Data Modeling & Transformation: Lead the team in building and maintaining robust data models using dbt and SQL that support complex analytics and reporting needs. Contribute directly as an individual contributor as needed.

• Snowflake Development: Oversee the design and optimization of the Snowflake data warehouse to ensure performance, scalability, and usability. Participate directly in key development efforts.

• Cross-Functional Collaboration: Act as the primary technical partner to analysts, business stakeholders, and data teams to deeply understand requirements and translate them into strategic engineering solutions and delivery plans.

• Performance Tuning: Guide the optimization of SQL queries and data transformations to improve execution speed and resource efficiency across the platform.

• Tooling & Automation: Identify, evaluate, and implement opportunities to automate data workflows, improve pipeline reliability, and establish a formal DataOps/MLOps framework using modern orchestration tools (e.g., Airflow, Prefect, cloud-native serverless functions).

• BI Tool Support: Ensure the team provides clean, well-structured data models to enable effective use of BI tools like Looker, Sigma, Tableau, or similar platforms.

• Pipeline Engineering: Direct the development and maintenance of scalable data ingestion pipelines that pull data from APIs and other sources into Snowflake, including exploring solutions for near real-time data feeds.

• Data Governance & Quality: Champion best practices in data governance, data lifecycle management, and dimensional modeling. Implement data validation checks, documentation standards, and lineage tracking to maintain high data integrity across all of our systems.

• Oracle Fusion Cloud Migration & Integration: Lead the complex data migration strategy for our active Oracle deployment. Architect, build, and maintain secure, high-performing data flows and syncs between Oracle and Snowflake to ensure operational continuity and analytical excellence.

OUR IDEAL CANDIDATE

• Experience: 8+ years in data engineering or related roles, with a strong focus on data modeling and pipeline development.

• Education: Bachelor’s degree in Computer Science, Engineering, Data Analytics, or a related field.

• Technical Skills:

  • Proven experience leading complex data migration or implementation projects.

  • Advanced proficiency in SQL and experience with data modeling (e.g., star/snowflake schemas).

  • Hands-on experience with dbt for building modular and testable data transformations.

  • Experience developing data pipelines using Python and workflow orchestration tools (e.g., Airflow, Prefect).

  • Deep understanding of Snowflake.

  • Demonstrated ability to design and implement a modern data architecture from scratch.

• BI & Analytics Tools:

  • Familiarity with BI platforms such as Looker, Tableau, or Sigma is helpful.

• Infrastructure & Governance:

  • Understanding of ELT/ETL workflows, data governance, and monitoring practices.

  • Experience defining and enforcing organizational standards for data quality, metadata management, and cost optimization within a cloud data warehouse (Snowflake).

• Communication & Problem Solving:

  • Ability to clearly explain technical details to both technical and non-technical stakeholders.

  • Strong analytical and debugging skills; attention to detail in code and data quality.