Senior Data Engineer (AWS)
Build and maintain scalable data pipelines in Python and SQL, orchestrated with Airflow and landing in AWS data lakes and warehouses.
Work on lakehouse patterns, data quality, observability, and secure-by-design delivery across batch and streaming workloads.
Responsibilities
- Build and maintain Python and SQL pipelines orchestrated with Airflow.
- Design and improve ingestion, transformation, and serving layers on AWS data lakes and warehouses.
- Implement and enforce data quality checks, data contracts, and schema evolution practices.
- Optimize large-scale batch and streaming jobs with Spark/PySpark and modern table formats.
- Apply CI/CD and infrastructure-as-code practices to data workflows.
- Improve observability with monitoring, alerting, and SLI/SLO thinking.
- Collaborate on secure handling of data, access control, and governance.
Requirements
- 5+ years of experience building production ETL/ELT pipelines at scale.
- Strong Python, SQL, and data modeling skills.
- Hands-on experience with Airflow and Apache Spark/PySpark.
- Practical AWS experience with S3 and data warehouse services.
- Experience with data quality frameworks, schema evolution, and CI/CD.
- Familiarity with Iceberg, Delta Lake, dbt, Kafka, or Kinesis is a plus.
- Experience in a regulated, high-scale, or analytics-heavy environment is a plus.
What will be your next steps?
Quick non-technical conversation
Our initial conversation is a brief, non-technical discussion to understand your background and career aspirations. We're keen to learn about your communication style and how you approach teamwork and decision-making.
60 to 90 minutes technical interview
This in-depth technical assessment, lasting 60 to 90 minutes, is designed to evaluate your specific skills and expertise. We will present you with challenges relevant to our client’s requirements.
Client interview
In this stage, you will meet directly with the client for a final technical discussion. This interview will be similar in format to our internal technical assessment, allowing the client to see firsthand how your expertise aligns with their specific project needs and team.
Offer
Congratulations on successfully completing our evaluation process. We are pleased to extend an offer and recommend you to our clients.
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