We are looking for a candidate with strong expertise in Databricks, Python, PySpark, SparkSQL, Delta Lake and experience to design and build data solutions for JLL's global real estate operations.
Responsibilities
- Translate Alteryx visual ETL logic into clean, optimized, code-based Databricks pipelines, ensuring full parity with source behavior.
- Recreate dynamic Alteryx behaviors such as parameter-driven execution and conditional logic in Databricks using PySpark.
- Validate migrated pipelines against source outputs and confirm measurable performance and scalability improvements post-migration.
- Design and develop ETL/ELT pipelines using PySpark, Delta Lake, and Databricks Workflows to process large-scale datasets efficiently.
- Produce clear technical documentation covering data flows, architecture decisions, and operational procedures; assist in developing communication materials to support accurate usage and interpretation of JLL data by business teams.
- Monitor data pipelines and Databricks workloads to support stability, performance, and reliability.
- Develop a thorough understanding of how data flows from various source systems and source types to continuously fine-tune data integration solutions.
- Collaborate with senior engineers to understand business requirements and contribute to appropriate technical solutions.
- Work independently or as part of a team to deliver data engineering projects on time and to specification; follow team coding standards and best practices and actively contribute to continuous process improvement.
Technical Skills & Competencies
- Databricks ETL/ELT Pipeline Design, Build & Optimization
- Python — Scripting, Automation, Pipeline Development
- PySpark — Distributed Processing, Transformations, Optimization
- Unity Catalog — Data Governance, Access Control, Lineage
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