Senior Data Engineer

Job Description

Senior Data Engineer

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Purpose of This Role

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The Senior Data Engineer is the primary builder and technical problem-solver for iDENTIFY's client data work. While the Senior Data Architect defines the patterns and standards, the Senior Data Engineer executes at the highest level of craft within them—and raises the quality of everything they touch.

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Where a Data Engineer works within a defined scope on a single engagement, the Senior Data Engineer operates across multiple concurrent work streams, anticipates complexity before it arrives, and actively improves the tools and practices the whole team relies on. This role is the technical backbone of client delivery.

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Builder + Executor + Multiplier. This role ships the work—and makes the work around it better.

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Apply Here:

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What This Role Owns

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Client Data Engineering

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This role is the hands-on technical lead for client engagements. That means more than writing good code—it means understanding the client's actual problem well enough to build something they can grow with.

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• Leads design, implementation, and maintenance of data pipelines and ETL processes for client engagements. Owns the quality and reliability of what ships.
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• 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.
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• 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.
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• Manages multiple concurrent client workstreams without dropping quality. Prioritizes effectively and communicates proactively when timelines are at risk.
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Pipeline Quality and Reliability

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At the senior level, engineering quality is a personal standard, not a process imposed from outside.

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• 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.
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• Implements data quality checks and validation logic as a standard part of delivery, not an afterthought.
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• Identifies performance bottlenecks and either resolves them directly or escalates with a clear diagnosis and proposed fix.
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• Thinks about failure modes during design. Builds pipelines that are observable and recoverable, not just functional.
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Reusability and Platform Contribution

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A Senior Data Engineer at iDENTIFY doesn't just solve the problem in front of them. They recognize when a solution has broader value and make it reusable.

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• 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.
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• Supports the code generator initiative by building ingestion logic that follows governance, traceability, and safety standards.
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• Identifies opportunities to standardize across clients and raises them with the Senior Data Architect or data team lead.
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Team Support and Knowledge Sharing

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Senior engineers make the people around them better. This is part of the job, not optional.

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• Provides technical guidance and troubleshooting support to other data engineers. When someone is stuck, you are a resource.
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• Documents what you build and what you learn. Lessons Learned entries are how the team avoids repeating expensive mistakes.
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• Participates in code reviews as both author and reviewer. Feedback is specific, actionable, and respectful.
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What We Expect

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Experience and Background

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This role requires depth, not just range.

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• 8+ years in data engineering with demonstrated end-to-end ownership of complex pipeline systems—not just contribution to them.
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• 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.
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• Strong proficiency in Python and SQL as primary tools. Pipeline development and scripting automation are daily activities.
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• Solid grounding in data modeling, database design, and warehousing. Normalization, indexing, and query optimization are applied instinctively.
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• Hands-on experience with ETL tooling and pipeline frameworks. Familiarity with modern data stack components—orchestration, transformation, observability—is expected.
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• Financial services or regulated data environment experience is a meaningful advantage given iDENTIFY's client base.
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How This Person Operates

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• Finishes what they start. Doesn't hand off half-built work or leave edge cases for someone else to discover.
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• Communicates early on risk. When a timeline is in jeopardy or a requirement is unclear, raises it before it becomes a problem—not after.
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• Reads the data. Doesn't just move data from A to B. Understands what it means, notices when it looks wrong, and asks the right questions.
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• Writes code others can understand. Readability and maintainability are professional standards, not optional courtesies.
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• Makes other engineers better. Answers questions generously, reviews work constructively, and shares context others would have to learn the hard way.
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Weekly Rhythm

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These are recurring, non-optional commitments:

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• Review tasks against timelines; surface blockers to project leads before they escalate.
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• Review pipeline and automation issues within your support scope; plan fixes with project leads or the data team lead.
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• Update architecture diagrams and process documentation in the Data Team Wiki.
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• Document and share Lessons Learned with the team.
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A Note on Seniority

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The distinction between a Data Engineer and a Senior Data Engineer at iDENTIFY isn't measured in years alone. It's measured in ownership.

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A Data Engineer executes assigned work with quality. A Senior Data Engineer is accountable for the outcome—anticipating problems, improving the systems they touch, supporting the people around them, and never treating "that's not my ticket" as an acceptable answer when something is clearly wrong.

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It also means showing up for clients. A Senior Data Engineer can walk into a client conversation, understand what they're trying to solve, and translate that into action. Technical skill matters—but earning a client's trust, communicating clearly, and helping them get unstuck is what separates good engineers from great ones at this level.

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• Client delivery quality is your professional reputation. Own it accordingly.
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