Lead the design, implementation, and testing of data systems, from architecture to production.
Build batch and real-time data systems that support business needs and critical products.
Ensure data systems' quality, performance, and stability through rigorous monitoring and quality assurance practices.
Design and optimize data models to efficiently meet business and product requirements.
Collaborate with cross-functional teams, including product managers, data scientists, and engineers, to develop scalable systems and drive data-driven decisions.
Maintain strong partnerships with backend, data science, and machine learning teams to ensure seamless integration of data systems.
Contribute to long-term data strategies and influence data engineering practices across the organization.
Mentor and guide team members, fostering best practices for data quality and governance.
Advance 3rd party data integrations, enhancing frameworks for data exchange, governance, and lineage.

9+ years of relevant experience with a Bachelor's/Master’s degree in CS/EE (or 6+ years with a PhD).
Extensive experience in designing, building, and operating distributed data platforms (e.g., Spark, Kafka, Flink) at a large scale.
Proficiency in Java, Scala, or Python, along with strong skills in data processing and SQL querying.
Proven track record of designing and optimizing batch and real-time data pipelines.
Strong collaboration skills with the ability to work with product managers, data scientists, and engineers.
Advanced problem-solving and analytical skills, with a focus on data quality, governance, and system reliability.
Excellent written and verbal communication, with the ability to influence stakeholders and convey complex technical concepts.
Expertise in data modeling, warehousing, and working with relational and columnar databases (e.g., PostgreSQL, MySQL, Redshift, BigQuery).
Experience with integrating machine learning models into data systems (preferred).
Strong leadership and mentorship capabilities, with experience guiding teams on best practices and technical strategies.
Flexible and innovative, with the ability to adopt new technologies to enhance data systems and processes.

Senior Data Engineer, BizTech

Key skills