What We Offer:
The Manager, Data Engineering leads a high‑performing, data‑centric team responsible for developing solutions that acquire, curate, and deliver trusted data to internal and external customers. This role partners closely with leaders and architects to design and mature enterprise data capabilities that support analytics, products, and operational decision‑making across the organization.
The Manager is accountable for building and scaling a modern data stack, supporting the full lifecycle from ideation and prototyping to launch, learning, and continuous improvement. This includes ownership of data transformations, data structures, metadata management, orchestration, dependency management, data quality, integrity, completeness, and workload optimization.
Schedule: 8:00AM – 5:00PM Monday- Friday (On call support, required as needed)
Location: Remote
Department: IT Enterprise Data Management
Key Responsibilities:
- Lead and manage a team of data engineers, ensuring goals, standards, and delivery commitments are met
- Collaborate with architects and business leaders to develop enterprise data engineering capabilities
- Oversee solutions supporting data ingestion, transformation, curation, and delivery
- Ensure strong practices for data quality, integrity, completeness, metadata, and dependency management
- Guide implementation of orchestration, workload management, and scalable data pipelines
- Assign resources to projects and tasks, balancing priorities and capacity
- Drive the continuous maturity of the modern data platform, promoting experimentation and iterative improvement
- Mentor engineers, provide career growth opportunities, and foster a culture of ownership, accountability, and innovation
- Model creativity, collaboration, and a positive “can‑do” attitude
Security & Compliance Responsibilities
As a member of the IT Department the Manager is responsible for secure information system management throughout the system lifecycle, including:
- Maintaining awareness of all information systems within scope of responsibility
- Understanding what sensitive data is stored, transmitted, or processed
- Enforcing the principles of least privilege and least functionality
- Recognizing events that may constitute an information security incident
- Understanding and participating in security incident response activities
What We're Looking For:
- Education: 4 Year / Bachelors Degree, required. Computer Science, Mathematics, Management Information Systems, or related field.
- Experience:
- 10 years Information technology experience, required.
- 4 years Data Engineering Development, required.
- 2 years Manager, Supervisor, Lead for IT Team, required.
- 2 years Designing for public cloud architecture, required.
- Additional Skills/Requirements Required:
- Capable of managing a team across multiple large projects simultaneously.
- Effectively manages multiple priorities with strong organization and planning skillset.
- Manage and monitor design, development and testing of data movement, transformation, extraction, migration, orchestration, and data pipeline activities using cloud based and on-premises tools.
- Proficient knowledge of SQL, Python, Pyspark, Spark SQL, APIs, Azure Data Factory, Azure Synapse, Databricks, Apache Airflow, Delta Lake, and Azure Functions, data lake query engines.
- Knowledge of principles of DevSecOps, DataSecOps.
- Leads research on emerging technologies to drive innovation to deliver a stable, scalable, and secure environment and effectively communicate solutions within the team and to various levels of management.
- Participate in key technical and design discussions with technical leads and architects.
- Collaborates with senior leaders and assists architects in defining roadmap.
- Provide assessment, strategies, advisory services and technical vision to prospects and customers as part of the data platform strategy.
- Leverage automation technologies to rapidly deliver environments while maintaining configuration management across the enterprise.
- Analyzes IT architecture requirements and systems/application compatibility to implement data pipelines across the Enterprise.
- Provides consistent and fair oversight by creating an environment that supports and respects diversity to promote creative problem solving.
- Demonstrates knowledge of process improvement principles and applies appropriately to improvement activities.
- Success Indicators:
- Data Engineering pipelines are successfully transitioned from on-premises to public cloud platform.
- Build a Center of Excellence team with maturity in Architecture, Security, Observability, DevOps, Community Engagement.
- Mentor team of engineers to drive innovation in all areas of data integration and platform engineering.
- Build a team that is customer centric, delivery-focused and results driven.
- Provide a remarkable and delightful experience to stakeholders, team members.