Our Data Platform Team Lead will drive innovation and build scalable data infrastructure that influences the heart health of thousands of users. In this role, you will manage a team of 4 senior data engineers & BI developers responsible for the end-to-end development of data product. You will work in close collaboration with other cross-functional teams, including analysts, data scientists, and engineers, to deliver high-quality solutions that drive data insights and business intelligence at scale. As team lead, you will guide and mentor your team ensuring they grow their skills and deliver impactful solutions. Your leadership will be critical in driving team productivity, technical excellence, and fostering an innovative culure.
Our Technologies stack: Python, Spark, Airflow, DBT, Kafka, AWS (Glue, EMR, S3, Athena and more), Docker, Kubernetes, MongoDB, Redis, Postgres, Elasticsearch, and more.
Responsibilities:
Leadership & Team Management: Lead, mentor, and manage a team of 5 senior data engineers. Foster a culture of collaboration, continuous improvement, and technical excellence.
Data Pipeline Development: Oversee the development and optimization of data pipelines and architectures to support our data flows. Ensure data processing is efficient, scalable, and aligned with business goals.
System Integration: Collaborate with cross-functional teams to integrate and optimize systems that retrieve and analyze data to influence user outcomes.
End-to-End Ownership: Take responsibility for the end-to-end development, deployment, and maintenance of our data systems, ensuring they meet business needs and industry standards.
Innovation & Continuous Learning: Stay up-to-date with emerging technologies and best practices. Identify opportunities to innovate and improve data systems and processes.
Collaboration with Stakeholders: Work closely with researchers, architects, and engineers to ensure that data systems align with research objectives and technical requirements.
Requirements: Bachelors Degree in Computer Science or related field
At least 4 years of management experience leading a team of engineers
7+ years working experience of designing and implementing server-side Data solutions
Proven experience in creating and optimizing big data processes, pipelines and architectures
Experience with AWS ecosystem
Experience working on production grade projects
Experience leading 3rd party POCs in the Data Engineering domain
Experience with Kubernetes in Production
Experience with Python or similar
Experience with Apache Airflow or similar
Familiarity with distributed systems and technologies (Spark, Hadoop, MapReduce)
This position is open to all candidates.
