Senior Data Engineer

iDENTIFY is a company focused on data engineering solutions, and they are seeking a Senior Data Engineer to lead client data work. This role involves designing and implementing data pipelines, ensuring quality and reliability, and contributing to reusable data solutions while supporting the team and clients effectively.

Responsibilities:

• Leads design, implementation, and maintenance of data pipelines and ETL processes for client engagements. Owns the quality and reliability of what ships
• Develops data models and databases that support client reporting and analysis—designed to hold up as data volumes and use cases grow, not just meet the immediate ask
• Conducts in-depth discovery with clients to surface real data requirements—not just what's asked for, but what's actually needed—and translates that into clean technical specifications
• Manages multiple concurrent client workstreams without dropping quality. Prioritizes effectively and communicates proactively when timelines are at risk
• Continuously monitors data processes for quality, reliability, and performance. Flags and fixes problems as a matter of course—doesn't wait to be assigned a ticket
• Implements data quality checks and validation logic as a standard part of delivery, not an afterthought
• Identifies performance bottlenecks and either resolves them directly or escalates with a clear diagnosis and proposed fix
• Thinks about failure modes during design. Builds pipelines that are observable and recoverable, not just functional
• Actively contributes to iDENTIFY's library of reusable data accelerators—pipeline templates, transformation patterns, testing utilities. If you build something useful, it shouldn't live only in one client's project
• Supports the code generator initiative by building ingestion logic that follows governance, traceability, and safety standards
• Identifies opportunities to standardize across clients and raises them with the Senior Data Architect or data team lead
• Provides technical guidance and troubleshooting support to other data engineers. When someone is stuck, you are a resource
• Documents what you build and what you learn. Lessons Learned entries are how the team avoids repeating expensive mistakes
• Participates in code reviews as both author and reviewer. Feedback is specific, actionable, and respectful

Requirements:

• 8+ years in data engineering with demonstrated end-to-end ownership of complex pipeline systems—not just contribution to them
• Client-facing or consulting experience strongly preferred. Translating client requirements into technical decisions—and explaining those decisions clearly—is a core part of this role
• Strong proficiency in Python and SQL as primary tools. Pipeline development and scripting automation are daily activities
• Solid grounding in data modeling, database design, and warehousing. Normalization, indexing, and query optimization are applied instinctively
• Hands-on experience with ETL tooling and pipeline frameworks. Familiarity with modern data stack components—orchestration, transformation, observability—is expected
• Financial services or regulated data environment experience is a meaningful advantage given iDENTIFY's client base