Senior Data Engineer

Senior Data Engineer
We are seeking a Senior Data Engineer to support the modernization of enterprise data systems that manage employees, store, and compensation-related data. You will focus on building a scalable, SOC-compliant architecture in BigQuery to unify logic, streamline pipelines, and deliver high-quality datasets for business units including retail, corporate, dealer, and call center operations. This is a hands-on role requiring strong technical depth, attention to compliance, and the ability to collaborate across cross-functional teams.
Senior Data Engineer Skills:

• 6+ years of experience in data engineering with strong relational and dimensional modeling skills
• 3+ years of experience with BigQuery and GCP tools such as Dataflow, Pub/Sub, and Cloud Storage
• Advanced SQL and Python skills for building and transforming data pipelines
• Experience integrating data from ERP, CRM, or legacy enterprise systems
• Familiarity with SOC-compliant or regulated data environments
• Experience with tools like Pulumi/Terraform for managing data pipelines, schemas, and permissions via GitHub
• Experience with enabling ‘zero-copy' data models, like BQ sharing/Analytics Hub, publishing datasets to consumption layers for internal subscribers
• Background in financial, compensation, or retail data domains preferred
• Experience working in Agile delivery teams using CI/CD tools such as GitHub, Airflow, Terraform
• Strong communication and collaboration skills across technical and business teams

• Experience working with compensation or incentive payout systems
• Familiarity with enterprise hierarchy or org structure data
• Exposure to data product development or building reusable data assets

• Design and implement scalable data pipelines using BigQuery and Dataflow
• Integrate and normalize complex datasets from various enterprise and legacy systems
• Translate business logic into well-structured, auditable SQL-based data transformations
• Build and maintain source-to-target mappings and orchestration for batch and real-time pipelines
• Deconstruct and re-architect a legacy codebase to build new modular, scalable, and supportable data solution
• Apply data modeling best practices to deliver clean, trusted, and maintainable datasets
• Collaborate with architects, engineers, and product owners to align on technical delivery
• Ensure pipelines meet data governance, compliance, and security requirements
• Support pipeline optimization, issue triage, and performance tuning
• Participate in Agile team ceremonies and contribute to a collaborative engineering culture