About the company
This position is listed on behalf of a partner company, which manages all applications and next steps. Our partner is looking for a Manager, Data Engineering based in the United States.
Responsibilities
- Lead, manage, and develop a team of at least five data engineers (hiring, onboarding, performance reviews, coaching, development)
- Translate enterprise data architecture strategy into roadmaps, prioritized backlogs, sprint plans, and measurable delivery outcomes
- Oversee day-to-day engineering execution: task breakdown, delegation, removing blockers, technical reviews
- Establish engineering standards for maintainability, consistency, documentation, and predictable delivery
- Drive implementation of the Medallion architecture (Bronze, Silver, Gold) using Azure Databricks, Spark, Delta Lake, SQL Server, dbt, Boomi, and Rivery
- Partner with the Data Architect to translate architectural principles into implementation patterns and guardrails
- Establish DataOps practices: CI/CD, branching and release strategies, code review standards, operational runbooks
- Improve pipeline observability and reliability (data freshness, failures, data quality monitoring, incident response)
- Collaborate with application and database teams on data access patterns for SQL Server (CDC, read replicas, snapshot isolation, batching)
- Design ingestion and transformation workflows for APIs, CDC-enabled databases, and file-based feeds
- Work with business stakeholders to clarify requirements and prioritize initiatives
- Build engineering culture through one-on-ones, feedback, mentoring, and succession planning
Requirements
- Bachelor's degree in Computer Science, Data Science, Engineering, or equivalent experience
- At least 10 years in software or data engineering, building production-grade data pipelines and platforms
- At least 2 years in a technical leadership capacity
- Direct people management experience (hiring, interviewing, onboarding, performance reviews, development)
- Deep hands-on expertise with Databricks, Apache Spark, Boomi or Rivery, and Delta Lake
- Strong experience designing ETL/ELT pipelines (ingestion, orchestration, transformation, delivery)
- Demonstrated experience implementing Medallion architecture with access controls
- Experience with upstream SQL Server systems (read replicas, CDC, snapshot isolation, batching)
- Strong understanding of data ingestion methods (APIs, database change streams, file drops)