About the Role We are looking for a Lead Data Engineer to design, build, and scale cloud native data infrastructure and pipelines that power analytics, reporting, and AI/ML initiatives. You will take technical ownership of our data platform, including architecture, ingestion, warehousing, and performance, with a strong emphasis on AWS and Snowflake, while mentoring engineers and partnering closely with analytics and platform teams.

What You Will Do

Architect, build, and maintain scalable ELT/ETL pipelines integrating data from many disparate sources into a centralized cloud data warehouse

Design and optimize Snowflake schemas, warehouses, and query performance, driving down processing times and controlling compute costs

Build and manage cloud infrastructure on AWS (compute, storage, orchestration, and managed data/ML services) in partnership with cloud engineering

Lead data pipeline orchestration using modern tooling (dbt, Airflow, Glue, or similar) to reliably feed dashboards, reports, and downstream applications

Establish and enforce data quality, security, and governance standards, including periodic audits of cloud data environments

Design and deploy data driven applications and pipelines in support of business and analytics use cases

Set up and maintain shared data environments (containerized data science/dev environments) supporting many concurrent users

Provide technical leadership across the data engineering function: setting standards, reviewing designs, and mentoring engineers

Required qualifications
What You Will Bring

7+ years of experience designing, building, and deploying data engineering pipelines and platforms

Deep hands on expertise with Snowflake and strong SQL skills across relational and cloud data warehouses

Strong experience with AWS cloud services for data engineering (compute, storage, orchestration, and managed services)

• Proficiency in Python for pipeline development and automation

Experience with modern ETL/ELT and orchestration tooling (dbt, Airflow, Glue, or similar)

• Familiarity with containerization (Docker, Kubernetes) for data environments

• Experience with BI/analytics platforms (Tableau, Power BI)

• Ability to design and support lightweight APIs/services for data delivery

Bachelor's degree in Computer Science, Information Technology, or a related field

Nice to Have

• Exposure to AI/ML tooling and workflows, including LLM based applications

• Relevant cloud or data engineering certifications

Prior consulting or client facing delivery experience across multiple industries

Skills
AI/ML SQL Tableau ETL/ELT AWS Power BI Docker Kubernetes Python
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