Senior Data Engineer supporting AI - enabled financial compliance initiative with data pipelines and ingestion processes. Collaborating with diverse teams in a mission - critical regulated environment.
About the role
- Senior Data Engineer designing and scaling data pipelines for a go-to-market platform. Build and own systems that create a high-quality first-party contact dataset.
Responsibilities
- Build the enrichment platform - Design and scale pipelines that process 100M+ contact records, integrating with large-scale contact data vendors.
- Own data quality - Build deduplication, entity resolution, and record matching systems that merge contacts from multiple sources into a single high-quality record.
- Optimize vendor economics - Create waterfall enrichment logic that maximizes coverage and freshness while minimizing per-record cost across a portfolio of data vendors.
- Ship freshness infrastructure - Build systems that detect job changes, flag stale records, and trigger re-enrichment to keep the dataset current.
- Instrument and measure - Create quality scoring, coverage dashboards, and accuracy metrics that give the business visibility into dataset health.
Requirements
- 5+ years of data engineering experience, including 2+ years working with contact data, enrichment systems, or data infrastructure.
- Deep experience with data vendor APIs and the economics of contact data (coverage rates, accuracy tradeoffs, cost per record).
- Expert-level SQL and data modeling skills, with experience designing schemas for large-scale entity datasets.
- Track record building production data pipelines using modern tooling (dbt, Airflow, Dagster, Spark).
- Experience with entity resolution, deduplication, and fuzzy matching at scale.
- Strong understanding of data warehousing (Snowflake, ClickHouse, BigQuery) and performance optimization.
- Business-minded: you understand that data quality directly impacts revenue and can articulate tradeoffs in terms the GTM team understands.
Benefits
- comprehensive benefits (including medical, dental, vision, and 401(k) options)
Job title
Job type
Experience level
Salary
Degree requirement
Tech skills
Location requirements
Data Architect leading the definition and construction of cloud data architecture for Kyndryl. Participating in significant technological modernization initiatives, focusing on Google Cloud Platform.
Senior Data Engineer driving data intelligence requirements and scalable data solutions for a global consulting firm. Collaborating across functions to enhance Microsoft architecture and analytics capabilities.
Experienced AI Engineer designing and building production - grade agentic AI systems using generative AI and large language models. Collaborating with data engineers, data scientists in a tech - driven company.
Intermediate Data Engineer designing and building data pipelines for travel industry data management. Collaborating across teams to ensure reliable data for analytics and reporting.
Data Engineer managing and organizing datasets for AI models at Walaris, developing AI - driven autonomous systems for defense and security applications.
Data Engineer designing and maintaining data pipelines at Black Semiconductor. Collaborating with process, equipment, and IT teams to support manufacturing analytics and decision - making.
Junior Data Engineer role focusing on Business Intelligence and Big Data at Avanade. Collaborating on data analysis and SQL queries in a supportive learning environment.
GCP Data Engineer designing and developing data processing modules for Ki, an algorithmic insurance carrier. Working closely with multiple teams to optimize data pipelines and reporting.
Data Engineer at Securian Financial optimizing scalable data pipelines for AI and advanced analytics. Collaborating with teams to deliver secure and accessible data solutions.