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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.
Job Responsibility:
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
Requirements:
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
Nice to have:
Experience with stream processing frameworks like Flink or Spark Streaming
Familiarity with DevOps, MLOps, and CI/CD best practices for data platforms
What we offer:
Competitive salary
Flexible work-life balance with a 5-day working Policy
Paid time off
Learning & Development bonus
Health coverage
Rewards & Recognitions
Event & Festivals celebrations
Ongoing training programs
Onsite opportunities
Recognition opportunities for open-source contributions