The partner company of Jobgether is looking to solve the problem of leading the data engineering practice, overseeing data engineering, analytics, machine learning, and data science initiatives across complex, large-scale projects in the United States.
Requirements
- Deep expertise with Databricks, Spark, and large-scale data processing; strong proficiency in SQL and Python.
- Experience designing and implementing scalable data warehousing and ETL/ELT pipelines.
- Solid understanding of cloud data platforms (AWS, Azure, GCP) and ability to architect solutions across multiple environments.
- Strong knowledge of data modeling, schema design, query optimization, data governance, security, and compliance best practices.
- Bonus experience: real-time streaming technologies (Kafka, Kinesis), machine learning pipelines/MLOps, additional programming languages (Java, Go, Scala), open-source contributions, or domain expertise in healthcare/fintech.
- 7–10+ years of experience in data engineering, ideally with experience leading teams in consulting or cross-functional product environments.
- Proven leadership in managing data engineers, data scientists, and analytics professionals.
Responsibilities
- Lead and manage the data engineering team, providing mentorship, guidance, and professional development support.
- Architect and oversee the design of scalable, secure, and high-performance data systems across cloud environments (AWS, Azure, GCP) and platforms (Databricks, Snowflake).
- Define and enforce engineering standards, best practices, code review processes, testing, and data governance across projects.
- Plan, estimate, and execute data engineering initiatives, ensuring alignment with business and client objectives.
- Ensure security, privacy, and compliance of all data systems and pipelines.
- Act as a hands-on contributor, writing code, creating architecture diagrams, and reviewing technical designs.
- Stay current with AI, machine learning, and data engineering trends, incorporating new technologies and frameworks into practice.
Other
- 7–10+ years of experience in data engineering, ideally with experience leading teams in consulting or cross-functional product environments.
- Proven leadership in managing data engineers, data scientists, and analytics professionals.
- Excellent communication and presentation skills, capable of influencing technical and non-technical stakeholders.
- Demonstrated ability to balance hands-on execution with strategic leadership.
- Flexible work arrangements, including remote options.
