Data Engineer

Data Engineer Innovien Solutions - 3.7 Cincinnati, OH Job Details 1 day ago Qualifications Databricks Data Integration (Data management) Cloud data warehouses Data migration 5 years Data structures MongoDB SQL Data quality management Redshift Senior level Cross-functional collaboration

Python Full Job Description 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, Postgre

SQL, SQL

Server), managing and querying structured data across multiple systems Nice to have: • 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