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