Senior Data Engineer

Growth Acceleration Partners•Colorado Springs, CO

11d•Remote

About The Position

We are seeking a Senior Data Engineer to take technical ownership of data quality, identity resolution workflows, and data governance within a large-scale enterprise analytics platform. In this client-facing role, you will bridge identity data processing with downstream analytical layers, ensuring data integrity, source-to-destination validation, and seamless data contract management. Operating with technical autonomy, you will collaborate with data analysts, platform engineers, and cross-functional stakeholders to establish repeatable data governance standards and troubleshoot complex data flows across medallion architectures.

Requirements

5+ years of professional software and data engineering experience building, profiling, and maintaining enterprise data pipelines.
Proven track record in identity resolution, entity matching, and data lineage validation within complex first-party data ecosystems.
Strong experience with modern cloud data architectures (Medallion architecture: Bronze, Silver, Gold layers) and enterprise data sharing protocols (e.g., Delta Share).
Demonstrated expertise writing advanced SQL, Python, and PySpark scripts to profile, transform, and validate large-scale datasets.
Hands-on experience developing data contracts, usage guidelines, and governance documentation using tools like Atlan and Confluence.
Advanced English proficiency (written and verbal).
Exceptional stakeholder communication skills with the ability to explain complex technical data anomalies to non-technical business leaders.
Meticulous attention to detail and a high standard for data accuracy and reliability.
Strong analytical problem-solving mindset with high technical curiosity and self-direction.
Collaborative mindset capable of bridging gaps between engineering, product, and business analytics teams.
SQL & Data Profiling: Advanced SQL mastery for complex join logic, data lineage tracing, data validation, and source-to-visual reconciliation.
Programming & Processing: Python and PySpark for data transformation, pipeline troubleshooting, and automated quality validation.
Data Architecture & Governance: Medallion architecture (Bronze/Silver/Gold), Delta Lake / Delta Share, Data Contracts, and Data Lineage tooling.
Pipeline Diagnostics: Diagnostic troubleshooting across cloud data warehouses, ETL/ELT pipelines, and distributed data environments.
Documentation & Tooling: Confluence, Atlan, Jira, or enterprise data catalog and data dictionary management platforms.

Nice To Haves

Prior experience in automotive, digital marketing, or customer data platform (CDP) environments.
Exposure to applied data science methodologies, predictive analytics, or identity resolution graph algorithms.
Experience working in client-facing technical delivery or data consulting roles within enterprise accounts.

Responsibilities

Profile and validate digital identity records, verifying correct table joins, identity mapping logic, and downstream propagation across data layers.
Establish and maintain formal data contracts, join patterns, usage guidelines, and technical documentation in central governance repositories.
Review high-impact business analyses prior to stakeholder delivery to identify methodological errors, data quality anomalies, or improper join logic.
Perform root-cause analysis on pipeline failures, missing data transformations, and downstream propagation breaks, coordinating fixes through engineering backlogs.
Serve as the technical consultative link between identity platform capabilities, core data engineering teams, and enterprise business analysts.
Define, track, and automate repeatable quality assurance checks across cloud data lakes and distributed data sharing feeds.