A contact in our network has shared an opening for a SQL Data Engineer at a Fortune 100 financial institution. This is a critical contract position, available for both mid-level and senior professionals, with a duration of 12 to 24 months. The role is a hybrid model, requiring on-site presence for three to four days per week in Charlotte, North Carolina. The successful candidate will join a dynamic technology team that is crucial for building and maintaining the scalable data pipelines that power mission-critical finance applications.

This position is ideal for a data professional who thrives on ownership, technical rigor, and effective communication. The primary responsibility of the engineer is to design, build, and manage robust SQL-based ETL pipelines. This involves a deep understanding of data extraction, transformation, and loading processes. A key part of the job is the use of AutoSys (or similar) for job scheduling and orchestration, ensuring that all data workflows run smoothly and on time. The engineer will also be responsible for collaborating with upstream data providers to troubleshoot any delivery or schema issues that may arise, guaranteeing the integrity of the data.

Beyond the technical execution, the role requires a strategic mindset. The engineer will be expected to translate complex data requirements into scalable engineering solutions, proactively identify and resolve any pipeline performance bottlenecks, and ensure the high availability and accuracy of data across all systems. Maintaining clear documentation of data flows and operational practices is also a crucial part of the job. The firm operates in an agile environment, so the engineer will participate in all agile ceremonies and report on dependencies and progress.

To be considered for this role, you must have a strong background in data engineering. A mid-level candidate should have at least 5 years of experience, while a senior-level candidate requires 7 or more years. A strong command of SQL and hands-on experience with ETL development are non-negotiable requirements. Experience using AutoSys or a comparable job control system is also essential. A proven background in supporting finance, banking, or enterprise tech environments is a key qualification. The role also demands clear and concise communication skills, especially for client-facing or lead-level engagements. While not required, experience with Python or Apache Spark, exposure to CI/CD, version control, and performance tuning, and familiarity with data quality, governance, and compliance are all highly valued. This position is not a fit for Big Data specialists who lack recent hands-on experience with SQL and traditional ETL systems.

This is an opportunity to leave your mark on systems that directly impact decision-making at an enterprise scale. The firm is offering a competitive pay rate, a quick interview process, and a chance to work on a 12- to 24-month contract.