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Data Engineer
Job Description:
Our customer is hiring a Data Engineer to join a highly visible team that sits in the middle of everything—owning the data and infrastructure that supports 70,000+ internal users across the business. This team plays a key role in keeping data clean, organized, and usable across internal systems. This person will build and enhance data pipelines within a modern cloud data environment, with opportunities to get into new Greenfield work. It’s a high-impact role where you’ll work across multiple systems, partner closely with engineering teams, and have a real hand in how data is structured.
Requirements:
- 5+ years of experience in Data Engineering, supporting enterprise-scale data environments across multiple systems and data sources
- Expert-level SQL skills (PostgreSQL preferred, some Microsoft SQL Server), writing complex queries, joins, stored procedures, and views to manipulate and transform large datasets
- Python experience, building and maintaining ETL pipelines to extract, transform, and load data from multiple enterprise sources
- AWS Redshift experience, working within a cloud data warehouse to store, optimize, and deliver data for reporting and downstream applications
- Experience with relational databases (MySQL, PostgreSQL, SQL Server), managing and querying structured data across multiple systems
Nice to have:
• Databricks experience to support scaling data processing as the platform grows
• Databricks experience to support scaling data processing as the platform grows
- Experience with orchestration tools (e.g., Rundeck, Lambda) to support scheduling and automation of data workflows
- NoSQL experience (MongoDB, DocumentDB, CosmosDB) to support future-state data architecture
Responsibilities:
- Clean up and tighten key datasets to support final migration efforts, ensuring data is accurate and usable across systems
- Write and optimize complex SQL queries, stored procedures, and data structures to support business-critical needs
- Build and maintain ETL pipelines using Python to move and transform data across multiple systems
- Work within AWS Redshift to manage and optimize how data is stored and accessed
- Partner with engineering teams to understand data needs and ensure data is structured in a way that supports the business
- Support ongoing improvements to the data environment as the team moves beyond migration into more scalable, long-term solutions
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