Sr Data Engineer

Cox Enterprises • Atlanta, GA

2d • $101,500 - $169,100 • Hybrid

About The Position

Cox Automotive’s Enterprise Platforms Data & Analytics organization owns the data pipelines, Snowflake data layers, and governed data products that support Finance, Sales, Marketing, Service, and AI initiatives. Data from enterprise sources is loaded into Snowflake through a metadata-driven AWS framework, modeled into conformed and mart layers, and made available to BI tools, downstream applications, and AI agents under governance and PII controls.

The Sr Data Engineer is a hands-on technical leader on a Data & Analytics delivery pod. The role builds and delivers production pipelines and governed views, strengthens quality through validation and peer review, helps production support teams resolve complex data incidents, and mentors onshore and offshore engineers. The engineer delivers datasets for BI and AI-assisted analytics and uses AI-assisted development responsibly.

This is a hybrid role, with the ability to work remotely part of the week. The position is based in Atlanta, Georgia, or requires willingness to relocate there at the candidate’s own expense. Travel is 5% and the work shift is day. Applicants must be authorized to work in the United States for any employer without current or future sponsorship.

Requirements

• Applicants must be currently authorized to work in the United States for any employer without current or future sponsorship; OPT, CPT, STEM/OPT, and visa sponsorship are not available now or in the future.
• Must be located in Atlanta, Georgia, or willing to relocate at own expense.
• Bachelor’s degree in Computer Science, Information Systems, or a related field, or equivalent practical experience.
• At least 4 years of experience in Data Engineering building production ETL/ELT pipelines, with strong Python and advanced SQL.
• Strong Snowflake skills, including schema and view design, MERGE and history-table patterns, bulk loading and external stages, role-based access, masking policies, warehouse sizing, and query profiling.
• Strong production experience with AWS data services, including serverless compute, object storage, workflow orchestration, database migration and CDC, NoSQL, query and catalog services, event scheduling, secrets management, and IAM.
• Experience with infrastructure as code and release automation, including CloudFormation or Terraform, Git branching strategies, and CI/CD pipelines with automated deployment of database objects.
• Experience ingesting heterogeneous sources, including relational databases and CDC, ERP and CRM systems, SaaS APIs, and flat files.
• Analytics data-modeling knowledge, including dimensional and denormalized models, conformed layers, and the responsibilities of raw, hub, and mart layers.
• Experience with data quality and observability, including validation frameworks, reconciliation, SLA and freshness monitoring, alerting, and root-cause analysis of late or partial loads.
• Knowledge of data security and governance, including PII identification and masking, least-privilege access, and metadata and lineage practices.
• Ability to work in an Agile Release Train using an Agile tracking tool, write clear user stories and acceptance criteria, and communicate status and risk to Product and Engineering leadership.
• Experience mentoring engineers and reviewing code; comfortable leading work across onshore and offshore teams.

Nice To Haves

• Hands-on experience with AI-assisted engineering tools and spec-driven development, including building reusable skills or agents for data tasks.
• Familiarity with Snowflake AI features, dynamic tables, and Model Context Protocol (MCP) access patterns for exposing governed data to AI agents.
• Experience with dbt, Apache Airflow, or similar orchestration and integration platforms.
• Experience with data catalog and governance tooling.
• BI semantic-layer experience and understanding of how data models support self-service analytics.
• Domain knowledge in automotive, finance, sales, marketing, or contact-center data.
• AWS Solutions Architect or Data Engineer certification, or SnowPro certification.
• Experience with large-scale platform migrations and legacy-code modernization.

Responsibilities

• Design, build, and operate metadata-driven ingestion and egress pipelines that load data from enterprise applications, databases, and third-party APIs into Snowflake using a shared, configuration-driven AWS framework.
• Deliver features end to end, from refined requirements through source onboarding, raw-to-hub modeling, SQL transformations, validation, and release through controlled multi-environment CI/CD.
• Build governed Snowflake consumption layers, including conformed and base views, business-specific models, marts, and role-based access, with PII masking and data-quality verification.
• Extend and harden shared libraries and frameworks for SLA monitoring, asset registration, alerting, connection management, and code generation so sources can be onboarded through configuration.
• Define and enforce data-quality, reconciliation, and peer-validation standards, including row-count, orphan, duplicate, and freshness checks that gate production promotion.
• Lead production readiness and support escalations with production support teams; diagnose stale or partially loaded tables, replication and ingestion failures, role and permission regressions, authentication changes, and month-end reporting issues.
• Migrate legacy code into domain-owned repositories with clear ownership, CI/CD, and catalog metadata.
• Use AI-assisted development tools and spec-driven development to improve throughput while maintaining review and testing standards, and help formalize team guardrails.
• Partner with Product Owners, architects, and business and AI teams to turn business questions into reliable, documented, governed datasets for BI and AI workloads.
• Mentor junior and offshore engineers, review pull requests against architecture and design standards, and contribute to shared standards for ingestion, modeling, governance, and cataloging.
• Produce documentation, runbooks, and operational playbooks, and maintain accurate work items, features, and dependencies for the Release Train.

Benefits

• Eligible employees may take paid vacation as they deem consistent with their duties, company needs, and obligations.
• Seven paid holidays annually.
• Up to 160 hours of paid wellness time annually for the employee or family members.
• Bereavement leave.
• Time off to vote.
• Jury duty leave.
• Volunteer time off.
• Military leave.
• Parental leave.
• Potential health care insurance, including medical, dental, and vision coverage.
• Potential 401(k) retirement planning benefits.
• Potential paid days off, including sick leave, parental leave, flexible vacation/wellness days, and/or PTO.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior