Lead Data Engineer
About The Position
We are seeking a Lead Data Engineer with deep, hands-on experience designing, building, and operating production-grade data platforms. This role is targeted at senior engineers who have personally implemented end-to-end data pipelines and can mentor junior engineers through example. The Lead Data Engineer will be responsible not only for delivery, but also for setting engineering standards, patterns, and best practices across the data platform. This is a highly technical role. Candidates must have real-world, production experience with modern ELT architectures, Snowflake, dbt, Qlik Replicate, Python-based pipeline development, and cloud-native services.
Requirements
- Bachelor’s Degree and a minimum of 6 years of experience in Advanced Data Engineering, data technologies, cloud platforms, and project or technical leadership OR High School Diploma or GED and a minimum of 10 years of experience in Advanced Data Engineering, data technologies, cloud platforms, and project or technical leadership
- Deep, hands-on experience designing, building, and operating production-grade data platforms.
- Personally implemented end-to-end data pipelines.
- Real-world, production experience with modern ELT architectures, Snowflake, dbt, Qlik Replicate, Python-based pipeline development, and cloud-native services.
Nice To Haves
- Designing and operating Medallion Architecture data pipelines
- Data ingestion using Qlik Replicate (CDC and batch)
- Custom Python data pipeline development
- dbt Mesh Architecture experience
- dbt Cloud transformations, testing, SQL, and Jinja templating
- Snowflake ingestion and platform features (Snowpipe, Tasks, Stored Procedures)
- Data governance in Snowflake including RBAC, Tokenization, and dynamic data masking
- Release management, code deployment, disaster recovery activities
- Cloud development using AWS or equivalent Azure services
Responsibilities
- Design, build, and operate data pipelines using Medallion Architecture (Bronze, Silver, Gold).
- Own ingestion, transformation, governance, testing, and publishing layers.
- Ensure reliability, scalability, performance, and cost efficiency of pipelines.
- Implement CDC and batch ingestion using Qlik Replicate.
- Design ingestion patterns for databases, files, and APIs.
- Build reusable Python-based pipeline components and frameworks.
- Develop dbt models using advanced SQL and Jinja templating.
- Implement automated testing for data quality, schema validation, and freshness.
- Enable CI/CD-driven transformation deployments.
- Implement Snowpipe, Tasks, Streams, and Stored Procedures.
- Design and enforce RBAC, dynamic masking, and tag-based access control.
- Ensure data security and compliance through platform-level controls.
- Build and deploy data components using AWS services such as S3, Lambda, ECS Fargate, Glue, DynamoDB, and IAM, or equivalent Azure services.
- Collaborate on CI/CD, infrastructure automation, and environment promotion.
- Serve as a technical leader and mentor junior and mid-level data engineers.
- Lead design discussions, code reviews, and technical decision-making.
- Establish and enforce engineering best practices and standards.
Benefits
- Competitive, thoughtfully designed and quality benefits program
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What This Job Offers
Job Type
Full-time
Career Level
Senior
