Data, Engineer

Design, develop, and maintain ELT/ETL pipelines to produce clean, structured, and reliable datasets.

Build and maintain data orchestration workflows using Apache Airflow.

Develop and test data transformations using SQL, Python, and PySpark.

Monitor pipeline execution, troubleshoot processing issues, and proactively address SLA risks.

Administer and maintain lakehouse, object storage, Apache Spark, and Trino environments.

Build and maintain CI/CD pipelines using Bitbucket and Jenkins.

Manage user access, roles, permissions, and resource quotas across data platforms.

Monitor platform performance, respond to incidents, and perform system upgrades and patching.

Optimize storage configurations, including partitioning, data formats, and data retention.

Collaborate with Data Integration, Data Engineering, BI, and Analytics Engineering teams to support data initiatives.

Maintain infrastructure documentation, operational procedures, and technical runbooks.

Participate in capacity planning, platform optimization, and cost-management initiatives.

Provide coverage and support for Data Integration activities during team absences or periods of increased workload.

ELT/ETL Pipeline Development

Apache Airflow Orchestration

SQL, Python & PySpark

Apache Spark & Trino

Lakehouse Architecture & Object Storage

CI/CD using Bitbucket & Jenkins

Data Platform Administration

Access, Role, Permission & Quota Management

Pipeline Monitoring & Incident Resolution

Performance & Storage Optimization

Location: Client Site