Manager, Data Engineering

About the role

In this role, you will manage a team of data engineers, focusing on the delivery of innovative data pipelines and products that meet business needs. You'll be responsible for translating complex requirements into scalable solutions while ensuring high standards of technical quality and documentation.

You will work closely with various teams, including business, analytics, and infrastructure, to manage dependencies and communicate delivery risks. Success in this position involves promoting accountability throughout the engineering lifecycle and maintaining continuity during system migrations.

The estimated salary range for this role is $55,177 to $156,700 USD, with potential for bonuses or commissions.

Skills that matter here

• data engineering: Your extensive experience in data engineering will be essential for designing and supporting production data pipelines.
• Databricks: You will provide hands-on leadership in using Databricks for data migration and integration.
• Apache Spark: Strong experience with Apache Spark will be crucial for developing scalable data solutions.
• PySpark: Your knowledge of PySpark will help in building efficient data processing frameworks.
• SQL: You will leverage SQL for managing and querying data across various platforms.
• AWS: Experience with AWS is required for integrating data into the cloud environment.

Who this role suits

• You have a strong background in data engineering and have previously led technical teams.
• You thrive in dynamic environments and can manage changing priorities and complex dependencies.
• You possess excellent communication skills, enabling you to collaborate effectively with business stakeholders.
• You are detail-oriented and committed to maintaining high standards in technical delivery and documentation.

From the employer

• Lead, coach, and develop a team of data engineers, establishing clear expectations for delivery, technical quality, documentation, and production support.
• Own the planning and delivery of data engineering initiatives across assigned business domains, balancing modernization, integration, operational support, and stakeholder priorities.
• Translate complex business requirements into scalable, reliable, and maintainable data pipelines, models, and data products.
• Provide hands-on technical leadership through architecture reviews, code reviews, troubleshooting, and guidance on Databricks, Spark, SQL, and lakehouse design.
• Establish and enforce engineering standards for bronze, silver, and gold data layers, data modeling, reusable frameworks, testing, source control, and CI/CD.
• Lead the migration and integration of data from legacy platforms, SAP, Salesforce, operational databases, APIs, and file-based processes into the AWS Databricks environment.
• Ensure data solutions include appropriate quality controls, reconciliation, observability, lineage, security, RBAC, and production monitoring.
• Partner with business, analytics, architecture, application, and infrastructure teams to clarify requirements, manage dependencies, and communicate delivery risks and tradeoffs.
• Maintain continuity for business-critical reporting and operational data processes during system migrations and organizational change.
• Promote ownership and accountability throughout the full engineering lifecycle, including requirements, development, deployment, documentation, incident resolution, and knowledge transfer.

• Bachelor’s degree in computer science, engineering, information systems, data science, or a related field, or equivalent professional experience.
• Significant experience in data engineering, including experience designing and supporting production data pipelines.
• Previous experience leading or managing data engineers, technical teams, or major data delivery workstreams.
• Strong hands-on experience with Databricks, Apache Spark, PySpark, and SQL.
• Experience building data solutions using lakehouse or medallion architecture patterns.
• Strong understanding of dimensional modeling, relational modeling, data warehousing, and analytical data product design.
• Experience working with cloud data platforms, preferably AWS.
• Experience with Git-based development, pull requests, code reviews, CI/CD, and controlled production deployment.
• Experience integrating data from enterprise applications, relational databases, APIs, and file-based sources.
• Demonstrated ability to operate effectively in environments with ambiguity, changing priorities, legacy systems, and complex dependencies.
• Strong written and verbal communication skills.
• Ability to work directly with business stakeholders and translate business processes into technical requirements.

• Estimated starting compensation range for this role is $55,177–$156,700 USD.
• Employees may be eligible for bonus or commission opportunities.
• Comprehensive benefits package, which may include a 401(k) savings plan with company contributions, medical, dental, and vision insurance, life and disability coverage, paid time off, tuition reimbursement, and other wellness programs, subject to eligibility requirements.