Opening for Business Data Analyst :: Contract :: Wilmington, DE

Dice is the leading career destination for tech experts at every stage of their careers. Our client, SOHO Square Solutions, is seeking the following. Apply via Dice today! Note: Only W2 Candidates will be Considered. Types of Work: ETL Development & Data Engineering... • Design, develop, and maintain robust ETL pipelines to aggregate and transform raw data into actionable datasets for control execution. • Optimize complex SQL queries and Python scripts to improve data processing speed and reliability across various database environments (Postgres, Snowflake, etc.). • Integrate disparate data sources-including unstructured JSON and relational warehouses-into a unified data layer for risk reporting. Automated Data Validation & Scripted QA... • Build and execute automated QA test suites using Python (e.g., PyTest, Great Expectations) to validate data completeness, accuracy, and timeliness. • Develop "Data-as-Code" testing frameworks to catch anomalies or schema drift before they impact downstream control processes. • Perform unit and integration testing on ETL code bases to ensure the logic reflects the underlying business and system rules. Data Governance & Lineage... • Manage data repositories and CI/CD pipelines to ensure seamless and governed deployment of data assets. • Drive adherence to data quality principles, including automated metadata capture and technical lineage mapping. • Evaluate integration points to ensure SQL logic accurately captures the state of the systems being reported on. General Responsibilities: • Pipeline Optimization: Identify bottlenecks in data delivery and implement Python-based solutions to automate manual data work. • Technical Partnership: Collaborate with Engineering and Ops to translate control requirements into technical specifications for ETL workflows. • Strategic Problem Solving: Use a quantitative mindset to solve data gaps, leveraging Python libraries for deep-dive analysis into data anomalies. • Communication: Clearly articulate technical risks and data discrepancies to non-technical stakeholders to drive remediation. Basic Qualifications: • Master's Degree in a quantitative or technical field. • Proven experience building and running ETL pipelines in a production environment. • Expert-level proficiency in Python and SQL, specifically for data manipulation and automated testing. • Experience with relational and non-relational databases (Postgres, MySQL, DynamoDB, Cassandra, or similar). Preferred Qualifications: • Experience building automated QA frameworks for data validation. • Hands-on experience with AWS services (S3, Glue, Lambda, IAM) to support serverless data processing. • Familiarity with data orchestration tools (e.g., Airflow, Prefect) and version control (Git). • Experience handling unstructured data (JSON) and transforming it for structured reporting.