DataStage Engineer (Google Cloud Platform)

DataStage Engineer (Google Cloud Platform) Remote 4-6 month contract to hire
DataStage, Google Cloud Platform and Snaplogic required Healthcare background preferred Pain Points: candidates who do not have the correct focus area (building the data pipelines), candidates who have not built something from scratch; either they are maintaining existing data workflows or processes in production, but not building.

• 2 Developers need experience in Datastage--have legacy ETL pipelines which they are migrating. This role will analyze the existing ETL pipelines, jobs, and replace in their modern stack: SnapLogic, Python, some Spark, some Dataflow.
• These 2 Developers need experience in DataStage (they have not been successful in upskilling from Informatica, Talend, etc.).

• Experience in SnapLogic is strongly preferred; they have found this to be more amenable to upskilling.
• Needs experience in Airflow or Cloud Composer orchestration, development of new DAGs from scratch.
• Development of data ingestion and ETL pipelines from scratch. Using SnapLogic primarily for data pipelines and integrations, but also Python, SQL, Dataflow, Spark.
• Needs experience in data warehousing, Google BigQuery.
• Not responsible for building out visualizations; another team handles
• Will be supporting data modeling, but not owning. Should have some experience in data modeling, data warehousing fundamentals.
• Understanding of analytics as a whole, how data moves from source, warehouse, semantic or reporting layer, models, and reporting/BI, but their hands-on focus will be around building data pipelines and orchestration.
• Proactive communicators, inquisitive people, problem-solvers, unafraid to make suggestions, ask questions. "Order taker" and "heads down" types of Engineers will not be a culture fit for the team.
• They have a list of other technologies in their environment in smaller amounts/more dispersed--any would be a "nice to have": i.e. Kafka, Java, Apache Beam, Alteryx, etc.