Build secure, repeatable data ingestion and transformation pipelines.
Implement data cleansing rules and produce auditable, reproducible outputs.
Establish Import/export patterns, handling data extracts, schema discovery, incremental loads, handling multiple source instances.
Strong ability to interpret and apply geographical context in data processing pipelines.

A strong Data Engineer is required to work on the Data Transformation workstream within Client`s Digital Screening.
Capability in data transformation-heavy pipelines from data-profiling to cleansing to standardization, conformance and publishing.
Advanced knowledge of SQL for profiling, joins/merges, deduplication, anomaly detection, and performance tuning.
Scripting knowledge in Python for automation, parsing, rules engines, and data quality checks.
Experience using Python packages for data wrangling (e.g. Pandas, Polars).
Experience with modern data tooling (for example, Spark, Azure Data Factory).
Proven experience working with geospatial data, including handling spatial formats.

Data Engineer

Key skills