Data Engineer

Team Computers

Mumbai, Ahmedabad District

On-site

INR 1,800,000 - 2,400,000

Full time

14 days+

Get more replies from employers

Send a job-specific resume in minutes.

Job summary

Team Computers is seeking a skilled Data Engineer to design, develop, and optimize enterprise-grade data pipelines within an on-premises, containerized data platform environment. The candidate should have strong expertise in Python, Apache Spark, SQL/PL-SQL, and container orchestration to support scalable data ingestion, transformation, and analytics workloads.

The role involves building and maintaining robust data solutions that enable Business Intelligence, Analytics, AI/ML initiatives, and

Qualifications

  • Bachelor's degree in CS/IT/Engineering or related field.
  • Certifications in Data Engineering technologies preferred.

Responsibilities

  • Design, develop, and maintain scalable ETL/ELT pipelines using Apache Spark (PySpark/Scala).
  • Develop data ingestion frameworks for structured, semi-structured, and unstructured data sources.
  • Deploy and manage containerized data workloads within OpenShift or Kubernetes environments.
  • Build and maintain Lakehouse architectures using Medallion Architecture (Bronze, Silver, Gold).
  • Implement data quality validation, monitoring, and alerting mechanisms.
  • Optimize Spark workloads for performance, scalability, and resource efficiency.
  • Develop and manage workflow orchestration using Apache Airflow.
  • Collaborate with Business, Analytics, DevOps, and Data Governance teams to deliver enterprise data solutions.
  • Ensure adherence to data governance, compliance, and security standards.
  • Participate in code reviews, troubleshooting, and performance tuning activities.

Skills

Python
Apache Spark / PySpark
SQL / PL SQL
OpenShift / Kubernetes
Airflow
Git / CI/CD
Data warehousing concepts
Delta Lake
Data quality frameworks

Education

Bachelor's degree in Computer Science, Information Technology, Engineering, or related field

Tools

Oracle DB
PostgreSQL
OpenShift
Kubernetes
Apache Airflow
Git
CI/CD pipelines
Delta Lake

Job description

Job Summary:

We are looking for a skilled Data Engineer to design, develop, and optimize enterprise‑grade data pipelines within an on‑premises, containerized data platform environment. The ideal candidate should have strong expertise in Apache Spark, Python, SQL/PL‑SQL, and container orchestration technologies to support scalable data ingestion, transformation, and analytics workloads.

The role involves building and maintaining robust data solutions that enable Business Intelligence, Analytics, AI/ML initiatives, and regulatory reporting across the organization.

Key Responsibilities:
  • Design, develop, and maintain scalable ETL/ELT pipelines using Apache Spark (PySpark/Scala).
  • Develop data ingestion frameworks for structured, semi‑structured, and unstructured data sources.
  • Deploy and manage containerized data workloads within OpenShift or Kubernetes environments.
  • Build and maintain Lakehouse architectures using Medallion Architecture (Bronze, Silver, Gold layers).
  • Implement data quality validation, monitoring, and alerting mechanisms.
  • Optimize Spark workloads for performance, scalability, and resource efficiency.
  • Develop and manage workflow orchestration using Apache Airflow.
  • Collaborate with Business, Analytics, DevOps, and Data Governance teams to deliver enterprise data solutions.
  • Ensure adherence to data governance, compliance, and security standards.
  • Participate in code reviews, troubleshooting, and performance tuning activities.
Required Skills
Technical Skills:
  • Strong experience in Python programming.
  • Hands‑on experience with Apache Spark (PySpark preferred; Scala is an advantage).
  • Expertise in SQL, PL/SQL, and relational databases such as Oracle and PostgreSQL.
  • Experience with Red Hat OpenShift (OCP) or Kubernetes.
  • Knowledge of Apache Airflow for workflow orchestration.
  • Experience with Git and CI/CD pipelines.
  • Understanding of Data Warehousing concepts and Lakehouse architecture.
  • Familiarity with Delta Lake or equivalent open‑source storage formats.
  • Experience with Data Quality frameworks and monitoring solutions.
Preferred Skills:
  • Exposure to Medallion Architecture (Bronze, Silver, Gold).
  • Experience working in large‑scale enterprise data environments.
  • Certifications in Spark, Kubernetes/OpenShift, Python, or Data Engineering technologies will be an added advantage.
Qualifications:
  • Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field.
  • Relevant certifications in Data Engineering technologies are preferred.
Soft Skills:
  • Strong analytical and problem‑solving skills.
  • Excellent communication and stakeholder management abilities.
  • Ability to work independently as well as in cross‑functional teams.
  • Strong ownership mindset with a focus on quality and timely delivery.
Get your free, confidential resume review.
or drag and drop your file here.
Similar jobs

Similar jobs worth comparing

Data Engineer
Data Engineer

Advance Career Solutions • Pune District, Chennai District, Bengaluru

Hybrid
INR 1,200,000 - 2,800,000
Data Engineer
Data Engineer

NARBA • Dadri

On-site
INR 600,000 - 900,000
Data Engineer_Spark/Scala
Data Engineer_Spark/Scala

Zorba AI • Maharashtra

On-site
INR 800,000 - 1,200,000
Data Engineer_Spark/Scala
Data Engineer_Spark/Scala

Zorba AI • Mumbai

On-site
INR 1,000,000 - 1,500,000
Senior Data Engineer
Senior Data Engineer

AagatiServe Pvt Ltd • Delhi

On-site
INR 1,800,000 - 2,400,000
Data Engineer_Spark/Scala
Data Engineer_Spark/Scala

Zorba AI • Kolkata District

On-site
INR 1,000,000 - 1,500,000
Data Engineer - Python
Data Engineer - Python

IntraEdge • Bengaluru

On-site
INR 600,000 - 1,200,000
Senior Data Engineer
Senior Data Engineer

SourcingXPress • Hyderabad

On-site
INR 1,500,000 - 2,500,000
Senior Data Engineer
Senior Data Engineer

GlobalNodes • Gurgaon

On-site
INR 1,500,000 - 2,100,000
Data Engineer
Data Engineer

Meril • Vapi

On-site
INR 800,000 - 1,200,000