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Mid-level data engineer title, metro locations, and common SQL/ETL skillset increase candidate competition.
Core data engineering skills transfer across industries, though financial-forensics experience increases domain bias.
Explicit 4-7 years plus mandatory SQL Server and SSIS skills make shortlisting relatively strict.
Lead design, development, and maintenance of scalable SQL Server databases and ETL processes using SSIS for data integration and transformation.
Oversee data pipeline development, ensuring high data quality, integrity, performance, and optimization of data models to support analytics and reporting.
Collaborate with stakeholders to translate business needs into technical solutions, manage workstreams, and guide junior team members to deliver evidence-based risk and forensic analytics solutions.
4 to 7 years of work experience in data engineering, database development, or data-related roles.
Strong proficiency with SQL Server, T-SQL, and ETL tools like SSIS for building and optimizing data architectures and pipelines.
Experience working with large datasets ensuring data quality, integrity, and performance optimization.
Work Experience Required: 4 to 7 years
Experience in financial services, consulting, or regulated environments with exposure to risk, compliance, or regulatory data initiatives.
Ability to manage multiple priorities in fast-paced settings and own end-to-end delivery of complex data engineering workstreams.
Strong stakeholder management with proven skill in translating complex business requirements into scalable technical data solutions.