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Salary
$21k – $26k per year
Location
In office (Ahmedabad)
Seniority
Senior · 5+ years exp
Employment
Full-Time

Confirmed on the employer's own hiring board on Oct 1, 2026. First seen by Alion on Aug 21, 2025. Krish TechnoLabs scores B on the Alion truth index.

Overview
Company
Impact
Profile match
Established in 2003, Krish is an award-winning, full-service AI-led digital experience agency that helps brands innovate, evolve, and thrive in their businesses by crafting experience-driven digital solutions!

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.
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