The Senior Data Engineer is a key technical leader responsible for architecting and building large-scale, enterprise-level data platforms. You will mentor junior engineers, define best practices, and drive the strategic vision for our data infrastructure.
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.
