Data Engineer with SSIS / Pyspark / Python

Job Tille: Data Engineer
Location: Remote
Duration: 6 month contract +

To find strong candidates who possess deep expertise across SQL, SSIS, and PySpark/Python. These technologies, while all relevant to data engineering, typically fall into different experience areas:

• SQL and SSIS are often found in professionals with traditional ETL and on-premise backgrounds.
• PySpark/Python are more common among engineers working in modern big data, cloud, or distributed computing environments.

Candidates who are strong in SSIS and SQL tend to have limited exposure to PySpark/Python, while those proficient in PySpark are usually focused on cloud platforms and lack hands-on SSIS experience.
- if you want to get combination of this tools listed then
1. Mid-or-Senior Level Data Engineers

• Have evolved from traditional BI/ETL tools (like SSIS) into big data frameworks (like PySpark).
• Typically worked on hybrid data environments (on-prem + cloud migration projects).

1. Data Migration Specialists

• Worked on modernizing legacy systems, so they retain SSIS + strong SQL skills and had to learn Python/PySpark for cloud-native platforms (e.g., Azure Databricks, AWS Glue).

1. Full-Stack Data Engineers (rare but valuable)

• Comfortable building data pipelines across tools use SSIS for legacy loads, SQL for transformations, and Python/PySpark for scalable processing.

Role Notes:

• Has 4 openings for Senior Data Engineers,
• Core needs are around ETL, using SSIS immediately for the ingestion of source data into Postgres.
• Will need PySpark, experience in building PySpark notebooks, for migration from Postgres to Databricks/Snowflake.
• Can have experience in either Databricks or Snowflake, knowledge of medallion architecture--curating and modeling data through Bronze, Silver, Gold layers to semantic/reporting layer.
• Responsible for supporting some modeling efforts--not full-blown data modelers but should know entity-relationship, dimensional models.
• Ingestion of data, deduplication
• Another team within Client is responsible for building the visualizations themselves.
• Do not quite have a data dictionary, in the process of analyzing and documenting all lineage. They know the data sources though.
• Considering Purview or Unity Catalog long-term.
• Needs all Senior Engineers, 6-8 years of experience, entirely hands-on and need to "hit the ground running"
• Healthcare experience is preferred to understand the data, data formats, compliance regulations, etc.

Must Have:

• ETL
• SSIS
• PySpark
• SQL
• Python
• Snowflake or Databricks
• Basics of data modeling

Nice to Have:

• Purview or Unity Catalog
• Healthcare experience