Data Engineer

Job Description

At GKM IT , we’re looking for a Data Engineer - Lead to shape and scale our data engineering function. In this role, you will lead a high-performing team, define technical strategy, and architect enterprise-scale data platforms. You’ll collaborate with senior leadership, drive cross-functional data initiatives, and ensure excellence in building scalable, secure, and reliable data systems. This position requires strong leadership, deep technical expertise, and a passion for advancing data capabilities across the organization.

Requirements

• 7+ years of experience in data engineering, including at least 2+ years in a leadership or lead role.
  

• Proven ability to lead and manage data engineering teams, provide mentorship, and drive strategic initiatives.
  

• Strong expertise in architecting enterprise-scale data platforms and multi-tenant infrastructure.
  

• Hands-on experience with data lake/warehouse solutions (Redshift, BigQuery, Snowflake, Delta Lake, Apache Iceberg).
  

• Expert-level proficiency in Python, SQL, and data modeling.
  

• Deep knowledge of distributed systems, data processing frameworks, and system design.
  

• Advanced experience with cloud platforms (AWS, GCP, Azure), infrastructure as code, and containerization.
  

• Strong background in real-time and batch data pipelines using Airflow, Kafka, Spark, Flink.
  

• Experience implementing data governance, lineage, quality frameworks, and observability standards.
  

• Skilled in performance optimization for queries, storage, and infrastructure at scale.
  

• Knowledge of CI/CD workflows, testing strategies, and deployment automation.
  

• Experience with streaming platforms (Kafka, Kinesis) and event-driven architectures.
  

• Proficiency with modern table formats (Apache Iceberg, Delta Lake) and lakehouse architectures.
  

• Demonstrated ability in strategic thinking, stakeholder management, and cross-team collaboration.
  

• Experience in budget planning, vendor management, and technical recruitment.
  

• Excellent communication and leadership skills to drive collaboration between Data, ML, Analytics, and Engineering teams.
  

Good to Have:

• Experience with DBT for data transformation and modeling.
  

• Familiarity with data observability tools (e.g., Monte Carlo, Great Expectations).
  

Benefits

We don’t just hire employees—we invest in people. At GKM IT , we’ve designed a benefits experience that’s thoughtful, supportive, and actually useful. Here’s what you can look forward to:

• Top-Tier Work Setup
  You’ll be equipped with a premium MacBook and all the accessories you need. Great tools make great work.
• Flexible Schedules & Remote Support
  Life isn’t 9-to-5. Enjoy flexible working hours, emergency work-from-home days, and utility support that makes remote life easier.
• Quarterly Performance Bonuses
  We don’t believe in waiting a whole year to celebrate your success. Perform well, and you’ll see it in your pay check—quarterly.
• Learning is Funded Here
  Conferences, courses, certifications—if it helps you grow, we’ve got your back. We even offer a dedicated educational allowance.
• Family-First Culture
  Your loved ones matter to us too. From birthday and anniversary vouchers (Amazon, BookMyShow) to maternity and paternity leaves—we’re here for life outside work.
• Celebrations & Gifting, The GKM IT Way
  Onboarding hampers, festive goodies (Diwali, Holi, New Year), and company anniversary surprises—it’s always celebration season here.
• Team Bonding Moments
  We love food, and we love people. Quarterly lunches, dinners, and fun company retreats help us stay connected beyond the screen.
• Healthcare That Has You Covered
  Enjoy comprehensive health insurance for you and your family—because peace of mind shouldn’t be optional.
• Extra Rewards for Extra Effort
  Weekend work doesn’t go unnoticed, and great referrals don’t go unrewarded. From incentives to bonuses—you’ll feel appreciated.

Requirements
7+ years of experience in data engineering, including at least 2+ years in a leadership or lead role. Proven ability to lead and manage data engineering teams, provide mentorship, and drive strategic initiatives. Strong expertise in architecting enterprise-scale data platforms and multi-tenant infrastructure. Hands-on experience with data lake/warehouse solutions (Redshift, BigQuery, Snowflake, Delta Lake, Apache Iceberg). Expert-level proficiency in Python, SQL, and data modeling. Deep knowledge of distributed systems, data processing frameworks, and system design. Advanced experience with cloud platforms (AWS, GCP, Azure), infrastructure as code, and containerization. Strong background in real-time and batch data pipelines using Airflow, Kafka, Spark, Flink. Experience implementing data governance, lineage, quality frameworks, and observability standards. Skilled in performance optimization for queries, storage, and infrastructure at scale. Knowledge of CI/CD workflows, testing strategies, and deployment automation. Experience with streaming platforms (Kafka, Kinesis) and event-driven architectures. Proficiency with modern table formats (Apache Iceberg, Delta Lake) and lakehouse architectures. Demonstrated ability in strategic thinking, stakeholder management, and cross-team collaboration. Experience in budget planning, vendor management, and technical recruitment. Excellent communication and leadership skills to drive collaboration between Data, ML, Analytics, and Engineering teams. Good to Have: Experience with DBT for data transformation and modeling. Familiarity with data observability tools (e.g., Monte Carlo, Great Expectations).

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