We are looking for a seasoned Data Engineering Manager who will help shape the future of our Data Platform. This role will involve leading a team of Data Engineers and will require hands-on contribution to the design, development, and maintenance of the platform.

In Short

Lead and mentor a team of data engineers to design, develop, and deploy scalable solutions.
Collaborate with product and business stakeholders to deliver data solutions that meet user needs.
Architect, build, and maintain data infrastructure, ensuring reliability, scalability, and performance across various data sources and platforms.
Implement Data Ingestion, Transformation, and Data Quality features to support Application Engineering, Analytics, and various Business Verticals across the organization.
Collaborate with Data Engineers, Architects, and Business Analysts in building data models to improve reliability and interpretability of data for analytical and business needs.
Define and enforce coding standards and document best practices within the team.
Actively contribute to the creation of design documents, assess technologies, and conduct Proof of Concepts (PoCs).
Experience supporting production jobs and mitigate issues within the defined SLA.
Partner with senior leadership to define Data Strategy, Roadmap and hiring for future needs.
Bring in a positive attitude and foster a culture that embraces continuous learning and Innovation.

Requirements

Bachelor’s or Master’s degree in computer science, Engineering, or a related field.
7+ years of experience in Data Engineering, with a track record of driving technical innovation and implementation of complex data solutions at scale.
3+ years of experience managing a team or as a team lead.
4+ years of Cloud Experience: Azure (preferred)/AWS/GCP.
3+ years of working with EDI or HIE standards (e.g. X12, HL7, and/or FHIR).
Proven leadership experience managing and developing data engineering teams, including team growth, skill development, and strategic project execution.
Proficiency in programming languages such as Python, with experience in Modern Data Technologies like Spark, Databricks, and Kafka.
Expertise with Microsoft SQL Server (preferred) or other relational databases.
Experience in building data lakes to support high speed querying by the end users.
Strong communication skills, with the ability to convey complex technical concepts to non-technical stakeholders.