This is a 6-12+ month contract opportunity with our client located in Minneapolis, MN. On-site requirement is 4 days per week. Candidates must be authorized to work in the United States without the need for sponsorship.We are seeking a Senior Data Engineer to join a fast-paced, growing data engineering team within a forward-thinking investment firm. This role is ideal for a technically skilled data professional with strong experience in SQL and Python , and a passion for building data pipelines, modeling, and delivering modern data solutions. You must be comfortable working with both structured and unstructured data, and have a strong interest in cloud technologies. While experience with AWS , DBT , and Snowflake is a plus, the team is open to training the right candidate in these tools.
Primary Duties
- Build and maintain scalable data pipelines using SQL and Python .
- Work with both structured and unstructured data to support analytical and operational use cases.
- Support cloud data engineering projects, especially those leveraging AWS (training available).
- Collaborate on data modeling and transformation efforts across teams.
- Assist with documentation, QA, and code reviews to ensure data quality and system reliability.
- Communicate effectively with engineers, analysts, and business partners to deliver timely data solutions.
- Continuously identify opportunities to optimize and improve data workflows.
Required Qualifications
- Strong experience with SQL and Python.
- Ability to work confidently with structured and unstructured data.
- Strong analytical thinking and problem-solving skills.
- Excellent written and verbal communication skills.
- Self-starter who is eager to learn and grow in a fast-moving environment.
Nice to Have Skills
- Experience with DBT (Data Build Tool).
- Familiarity with Snowflake or similar cloud data platforms.
- Exposure to AWS services (e.g., S3, Redshift, Glue, Lambda).
- Experience with data visualization tools such as Looker (training provided).
- Knowledge of version control (Git), CI / CD, and workflow orchestration tools like Airflow.
- Background in financial services or data-intensive business environments.
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