Senior Data Engineer (Remote)

We are actively seeking Senior Data Engineers - experienced in building data pipelines and integrations from 3rd party data sources by writing custom automated ETL jobs using Python. The role will work in partnership with other members of the Business Analytics team to support the development and implementation of new and existing data warehouse solutions for our clients. This includes designing database import/export processes used to generate client data warehouse deliverables.

Skills:- ETL, SQL, Python / Pyspark, Amazon Web Services (AWS) / Azure Cloud.

Requirements

• 2+ Years experience as an ETL developer with strong data architecture knowledge around data warehousing concepts, SQL development and optimization, and operational support models.
• Experience using Python to automate ETL/Data Processes jobs.
• Design and develop ETL and data processing solutions using data integration tools, python scripts, and AWS / Azure / On-Premise Environment.
• Experience / Willingness to learn AWS Glue / AWS Data Pipeline / Azure Data Factory for Data Integration.
• Develop and create transformation queries, views, and stored procedures for ETL processes, and process automation.
• Document data mappings, data dictionaries, processes, programs, and solutions as per established standards for data governance.
• Work with the data analytics team to assess and troubleshoot potential data quality issues at key intake points such as validating control totals at intake and then upon transformation, and transparently build lessons learned into future data quality assessments
• Solid experience with data modeling, business logic, and RESTful APIs.
• Solid experience in the Linux environment.
• Experience with NoSQL / PostgreSQL preferred
• Experience working with databases such as MySQL, NoSQL, and Postgres, and enterprise-level connectivity experience (such as connecting over TLS and through proxies).
• Experience with NGINX and SSL.
• Performance tune data processes and SQL queries, and recommend and implement data process optimization and query tuning techniques.