Senior Manager, Data Engineering

This is a fully remote position, open to applicants in Michigan.

📋 Description

• Direct the architecture and delivery of Data Platforms.

• Take responsibility for the technical direction and implementation of cloud-native data platforms leveraging Databricks and AWS.

• Spearhead the design and execution of Lakehouse architecture—Delta Lake, Unity Catalog, and Spark-based processing—across client projects.

• Ensure that scalability, performance, security, and cost efficiency are integrated into solutions from the outset, rather than being addressed post-delivery.

• Construct and Refine Data Pipelines.

• Manage ingestion, transformation, and orchestration processes for both batch and streaming workloads.

• Utilize AWS-native services (Glue, Step Functions, Lambda, Redshift, S3) in conjunction with Databricks to develop dependable, production-level pipelines.

• Create reusable pipeline patterns and delivery accelerators to enhance consistency across the team.

• Facilitate AI, ML, and GenAI Use Cases.

• Guarantee data is accessible, reliable, and ready for production to assist in model development and deployment for AI and GenAI projects.

• Collaborate closely with data science and analytics teams to align platform capabilities with current and future AI initiatives.

• Participate in client AI roadmap discussions by translating platform decisions into clear strategies for enablement.

• Engage Clients on Technical Strategy.

• Take part in client-focused architecture reviews and technical strategy sessions, effectively communicating complex platform concepts as tangible business outcomes.

• Assist senior leadership in executive briefings, aiding clients in making informed decisions regarding platform direction and investment.

• Collaborate with strategy and delivery teams to define and structure data platform engagements.

• Develop the Data Platform Team.

• Lead, mentor, and nurture a team of data engineers, architects, and platform specialists.

• Establish technical standards and cultivate an environment where craftsmanship and continuous improvement are prioritized.

• Identify skill gaps and contribute to enhancing the team's capabilities alongside the expansion of OneMagnify's data practice.

⛳️ Requirements

• Over 7 years of experience in data engineering, data architecture, or analytics, with a minimum of 2 years in a leadership role.

• Demonstrated hands-on experience with Databricks in production settings (Delta Lake, Unity Catalog, Spark).

• Extensive experience with AWS data services—Glue, Redshift, S3, Lambda, Step Functions—in production environments.

• Strong knowledge of modern data patterns: Lakehouse architecture, ELT/ETL, streaming, APIs, and pipeline orchestration.

• Solid understanding of AI/ML and GenAI ecosystems, including data prerequisites for model development and deployment.

• Capacity to lead technical teams, communicate effectively with client stakeholders, and ensure high-quality delivery across projects.

🏝️ Benefits

• Medical, dental, and vision coverage.

• 401(k) retirement plan.

• Paid holidays.

• Flexible Time Off (FTO).

• Additional programs aimed at wellness, financial security, and professional growth.