Data Engineer to build and optimize -scale data processing systems using Apache Spark

Hours:

37.5

Contract:

6 months + possibility of extension
Work Model: 4 days onsite a week

• Strong Python with PySpark for building data solutions
• Hands‑on experience with Apache Spark in cloud‑native environments
• Expertise working with large‑scale data systems and modern formats such as Parquet and Iceberg
• Experience using Databricks for development and optimization

• Experience with AWS data services such as Glue or Lake Formation
• Knowledge of workflow orchestration tools like Airflow
• Background in distributed data processing architectures
• Exposure to capital markets or financial data environments

• Develop and optimize Spark‑based workloads in a cloud setting
• Work with large‑scale datasets using productive storage and table formats
• Collaborate with stakeholders to translate data requirements into engineering deliverables
• Ensure high availability, reliability, and maintainability of data platforms
• Contribute to production readiness through monitoring, documentation, and deployment
• Operate independently with minimal supervision to deliver complex data solutions
• Proactively manage risks and communicate progress to project leads

Disclaimer
AI may be used in evaluating candidates.
This posting is for an existing vacancy.