About the role
What You’ll Be Doing
- Design and architect complex, scalable, and reliable data pipelines and data warehouses.
- Lead the development and maintenance of ETL/ELT processes for high-volume, real-time, and batch data.
- Spearhead the adoption of new technologies and methodologies to improve data platform efficiency and performance.
- Mentor and guide a team of data engineers, fostering a culture of technical excellence and innovation.
- Collaborate closely with data scientists, analysts, and business stakeholders to define data strategy and requirements.
What We’d Love To See
- 5 - 10 years of experience in data engineering, with a proven track record of designing and implementing large-scale data solutions.
- Expert-level proficiency in SQL and at least one programming language (Python, Scala, or Java).
- Deep knowledge of big data technologies like Spark, Kafka, and distributed systems.
- Extensive experience with cloud data platforms (AWS, Azure, GCP) and data warehousing solutions (Snowflake, BigQuery, Redshift).
- Demonstrated experience in leading projects and mentoring junior team members.
It’d Be Great If You Had
- Experience with stream processing frameworks like Flink or Spark Streaming.
- Familiarity with DevOps, MLOps, and CI/CD best practices for data platforms.