Job Summary
We are looking for an experienced Data Engineering Lead to provide technical leadership across multiple data engineering projects and squads.
The ideal candidate will have strong hands-on experience with Apache Airflow, DBT, Python, SQL, and AWS, along with proven experience designing scalable data pipelines and leading data engineering teams.
You will be responsible for developing and optimizing Airflow workflows, managing DBT infrastructure, improving data engineering architecture, and ensuring reliable, scalable, and cost-effective data solutions.
Key Skills
Must Have:
Apache Airflow, DBT, Python, AWS (ECS/Fargate/EC2/EKS), SQL, React/JavaScript
Nice to Have:
ETL/ELT, Enterprise Data Warehousing, Data Architecture, Git,
Key Responsibilities
- Provide technical leadership across data acquisition, transformation, and distribution.
- Lead, mentor, and coach Data Engineers, Data Architects, and Database Administrators.
- Design, implement, and manage scalable data pipelines using Apache Airflow.
- Develop, test, and maintain complex Airflow DAGs and custom operators.
- Monitor, troubleshoot, and optimize Airflow workflows for performance and reliability.
- Develop, test, and maintain DBT infrastructure and models executed through Airflow.
- Manage DBT infrastructure upgrades and optimize DBT code for performance and efficiency.
- Integrate DBT workflows with Apache Airflow.
- Ensure data quality, integrity, reliability, and consistency across data pipelines.
- Collaborate with Data Engineers, Data Scientists, Product Owners, and other stakeholders to translate requirements into scalable solutions.
- Recommend improvements to data engineering architecture, frameworks, and technologies.
- Drive adoption of modern ETL/ELT, workflow orchestration, and data management practices.
- Document workflows, processes, configurations, and technical solutions.
- Troubleshoot production issues and drive continuous improvement.
AWS Infrastructure Responsibilities
- Manage and optimize AWS infrastructure supporting Apache Airflow.
- Hands-on experience with Amazon ECS, AWS Fargate, Amazon EC2, and Amazon EKS.
- Ensure Airflow infrastructure is scalable, reliable, secure, and cost-effective.
- Troubleshoot infrastructure, deployment, and performance issues.
- Support cloud infrastructure optimization and automation.
Required Skills & Experience
- Strong experience in Data Engineering and Enterprise Data Warehousing.
- Proven hands-on experience with Apache Airflow.
- Strong experience designing and maintaining complex Airflow DAGs.
- Experience developing custom Airflow operators.
- Expert-level experience with DBT (Data Build Tool).
- Experience managing DBT infrastructure upgrades and optimizing DBT code.
- Strong Python programming skills.
- Strong SQL and relational database experience.
- Experience with React or JavaScript frameworks.
- Strong understanding of ETL/ELT concepts and data pipeline architecture.
- Hands-on experience with AWS data and infrastructure services.
- Expert experience with ECS, Fargate, EC2, and EKS.
- Experience with Git and version control.
- Strong understanding of data quality, monitoring, troubleshooting, and performance optimization.
- Excellent problem-solving, communication, and collaboration skills.
- Proven experience mentoring and leading technical teams.
Nice to Have
- Experience with modern data architecture and cloud-native data platforms.
- Experience working with Data Science and Machine Learning teams.
- Experience with CI/CD and infrastructure-as-code tools such as Terraform.
- Experience with Agile/Scrum methodologies.
Leadership & Soft Skills
The successful candidate should be:
- A strong technical leader and mentor.
- Customer-focused and passionate about solving complex problems.
- Collaborative and comfortable working across technical and business teams.
- Comfortable communicating with senior leadership.
- Curious, innovative, and willing to experiment and learn from failures.
- Focused on outcomes, continuous improvement, and delivering business value.