Data Engineer – Lakehouse (PySpark / Databricks / Airflow / AWS)

Posted yesterday

sri techFort Worth (TX)

Data Warehousing SpecialistsComputer Systems Design Services

SENIORITY

Senior

About the role

Overview In this role you design, build and optimize data pipelines for a Lakehouse architecture using PySpark on Databricks, with Airflow orchestrations and AWS services. You’ll manage Delta Lake layers (bronze/silver/gold) and enforce governance while improving reliability, performance and cost. You work closely with cross-functional teams to support analytics, reporting and regulatory needs. This is a hands-on role in a software-focused environment that values scalable data infrastructure and cloud-native best practices. Responsibilities Design, build and optimize ETL/ELT pipelines using PySpark on Databricks Manage Apache Airflow DAGs for scheduling and workflow orchestration Ingest and transform data into Delta Lake (bronze/silver/gold layers)Leverage AWS services (S3, EC2, Lambda, IAM) for data integration Implement data modeling, schema enforcement, and governance Monitor and improve pipeline reliability, performance, and cost efficiency Key requirements Proficiency in PySpark and Databricks (Delta Lake, clusters, jobs)Hands-on with Apache Airflow (DAG design, monitoring)Strong AWS services: S3, EC2, Lambda, IAMStrong SQL and Python for transformations and orchestration Knowledge of Lakehouse architecture (Delta Lake) and data modeling Experience in ETL/ELT and data warehousing best practices PySpark Databricks Delta Lake Apache AirflowAWS S3AWS EC2

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