We are seeking an innovative Senior Data Engineer to join our Startup AI and Data Analytics Business Unit. This role is a critical bridge, connecting technical engineering with business strategy. Beyond just managing tickets or building pipelines, you will take full ownership of the data ecosystem. You will play a pivotal role in supporting our AI/ML initiatives , managing the modern data stack while simultaneously answering critical business questions to ensure data accessibility, reliability, and scalability.
WHAT YOU'LL DO:
Ecosystem Ownership & Strategy
Own the Data Ecosystem: Build and maintain robust data pipelines and ETL processes, taking full responsibility for the health, cost, and observability of the stack to prevent downtime before it impacts stakeholders.
Business-First Data Modeling: Design and manage data warehouses to support advanced analytics, focusing on creating "Gold Standard" data models that make self-service easy in platforms like PowerBI, Tableau, and Sigma.
Documentation & Governance: Maintain comprehensive documentation of all data engineering processes to enable stakeholder self-service, following the industry’s best practices.
Engineering & Execution
Infrastructure Development: Design and manage data lakes, warehouses, and databases to support advanced analytics and AI workflows.
Performance Tuning: Act as a SQL/Python expert to optimize data pipelines and troubleshoot issues proactively, ensuring queries are efficient and scalable.
Data Quality Management: Implement frameworks that ensure data reliability across the organization, ensuring smooth integrations across systems.
Analytics Translation & Collaboration
Bridge the Gap: Collaborate with cross-functional product, engineering teams, and customers to translate vague business goals into precise technical requirements.
Support AI/ML: Create models that specifically enhance Analytics and AI/ML projects.
WHO YOU MIGHT BE:
We know that great talent comes from many backgrounds. If you are a technical expert who cares about the business "why," we want to hear from you.
The Product-Minded Engineer: You are a Senior Data Engineer who is tired of just "taking tickets." You want to understand the business strategy behind the data and take ownership of the full lifecycle.
The Analytics Architect: You have a background in BI or Analytics but have grown into a "Ninja-level" technical expert in SQL and Python. You build pipelines not just to move data, but to answer questions.
The Startup Builder: You have worked in small teams driving innovative solutions and are comfortable wearing multiple hats—from architecting infrastructure to troubleshooting a dashboard.
WHAT YOU'LL BRING:
5+ years of experience in data engineering roles, including taking ownership of pipelines and optimizing infrastructure.
Technical "Ninja" Skills: Ninja-level proficiency in SQL (specifically CTE optimization) and Python (complex scripting and ML/AI).
Pipeline Architecture: Expertise in architecting data pipelines and ETL processes, with tools like Fivetran, Snowflake, and DBT.
Business Intuition: Proven ability to apply business intuition, leveraging analytical skills to present complex data insights and actionable recommendations to technical and non-technical stakeholders.
Visualization Proficiency: Experience building visual data analytic business-driven solutions using tools like PowerBI, Sigma, or similar analytic tools.
Masters degree in engineering or analytics
WHAT WOULD ALSO BE AWESOME:
Cloud & Big Data: Familiarity with cloud platforms like AWS and experience with big data technologies such as Snowflake.
Leadership: Proven experience in leading data engineering projects and integrating data from multiple sources.
Small Team Experience: You have worked in small teams driving innovative solutions and thrive in agile environments.
