Data Engineer Lead

We’re looking for a hands-on Data Engineer Lead to support an important Phase 0 discovery effort for contact identity, golden record, and marketing data model readiness. This role is ideal for someone who enjoys digging into complex data landscapes, partnering with cross-functional teams, and turning discovery findings into clear engineering handoff materials for Databricks build work.

Responsibilities

• Inventory priority source systems, data entities, identifiers, fields, relationships, and known data quality concerns.
• Review source documentation, sample data structures, field inventories, and SME input to understand the current data landscape.
• Assess data completeness, duplicates, freshness, conflicts, availability, lineage, and source reliability.
• Support source-to-target mapping for a canonical marketing data model.
• Translate identity rules, survivorship logic, source hierarchy, field ownership, account matching, and exception handling into engineering-ready inputs.
• Document data gaps, dependencies, assumptions, risks, and open questions for the internal engineering team.
• Help define acceptance criteria, data quality thresholds, and match-confidence considerations for the final handoff package.
• Partner with strategy and architecture stakeholders to ensure outputs are actionable and ready for Databricks implementation.

Skills

• 5+ years of experience in data engineering, data platforms, or a related field.
• Strong background in data discovery, profiling, mapping, and engineering handoff work.
• Hands-on experience with Python and PySpark.
• Strong Databricks experience.
• Experience with SQL and NoSQL databases.
• Experience working in enterprise data environments.
• Knowledge of ETL/ELT processes, data integration, and data modeling.
• Hands-on experience with AWS or another major cloud platform.
• Strong analytical, problem-solving, and communication skills.

Preferred Skills

• Experience with cloud data tools such as AWS Glue or Azure Data Factory.
• Familiarity with modern data architecture principles, including data lakes or data mesh.
• Exposure to governance, security, and compliance practices in data environments.
• Experience with performance optimization and scalable data solutions.
• Certifications in cloud data technologies are a plus.
• Ability to work collaboratively in a hybrid, fast-moving environment.

Benefits

• Medical, dental, and vision coverage.
• Retirement benefits.

Pay

The pay range for this role is $51 - $89 per hour based on qualifications and experience.