More jobs:
ELT Data Lead
Job in
Troy, Oakland County, Michigan, 48083, USA
Listed on 2026-07-26
Listing for:
Ampstek
Full Time
position Listed on 2026-07-26
Job specializations:
-
IT/Tech
Data Engineering, Data Warehousing
Job Description & How to Apply Below
We are seeking an experienced ELT Data Lead to lead the design, development, and optimization of modern cloud-based ELT data pipelines. The ideal candidate will have strong expertise in cloud data platforms, data warehousing, SQL, dbt, and orchestration tools. This role involves leading data engineering initiatives, mentoring team members, collaborating with business stakeholders, and ensuring high-quality, scalable data solutions.
Key Responsibilities- Lead the design and implementation of scalable ELT pipelines for enterprise data platforms.
- Design and optimize data models using dimensional modeling and star/snowflake schemas.
- Build and maintain data ingestion, transformation, and orchestration workflows.
- Develop and optimize SQL-based transformations using ELT best practices.
- Work with cloud data warehouses such as Snowflake, Databricks, Google Big Query, Amazon Redshift, or Azure Synapse.
- Implement transformation frameworks using dbt or similar ELT tools.
- Develop automated data quality checks, validation, and monitoring processes.
- Collaborate with data architects, business analysts, BI developers, and application teams.
- Optimize pipeline performance, cost, and scalability.
- Ensure data governance, security, and compliance standards are followed.
- Mentor junior data engineers and conduct code reviews.
- Troubleshoot production issues and support ongoing platform enhancements.
- 10+ years of experience in Data Engineering or Data Warehousing.
- 6+ years leading ELT-based data engineering projects.
- Strong SQL programming and query optimization skills.
- Hands-on experience with dbt.
- Experience with cloud data warehouses:
Snowflake Databricks Big Query Redshift - Experience with orchestration tools:
- Strong understanding of ELT architecture and modern data platforms.
- Experience with Python for automation and data engineering.
- Knowledge of Git, CI/CD, and Dev Ops practices.
- Experience with data quality, lineage, and metadata management.
- Strong leadership, communication, and stakeholder management skills.
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