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Lead Data Engineer

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Summary

Lead Data Engineer in Ahmedabad (on-site) who designs, builds, and optimizes scalable data pipelines and cloud-native data platforms for client projects. Core stack: Python, SQL, PySpark/Scala, AWS/Azure/GCP data services, Snowflake/Databricks/Delta Lake, Kafka streaming, and Airflow/dbt orchestration, plus team leadership and mentoring.

Job Purpose:


Design, build, and optimize scalable data engineering solutions that enable reliable, high-performance data platforms. Lead the development of modern data pipelines, cloud-native architectures, and data infrastructure while collaborating with cross-functional teams to deliver robust, client-focused data solutions.


Who You Are:


  • 8+ years of experience in Data Engineering, with at least 2+ years in a Technical Lead or supervisory role
  • Prior experience working in software services, IT consulting, or agency environments, managing multiple client engagements
  • Strong proficiency in Python, SQL, and PySpark or Scala for large-scale data processing
  • Hands-on experience with at least one major cloud platform (AWS, Azure, or GCP) and its data ecosystem (e.g., AWS Glue, Redshift, EMR, Azure Data Factory, Synapse, GCP BigQuery)
  • Advanced experience working with modern data platforms such as Snowflake, Databricks, or Delta Lake
  • Strong expertise in designing and building scalable ETL/ELT pipelines and data transformation workflows
  • Experience with workflow orchestration tools such as Apache Airflow, dbt, or Prefect
  • Hands-on experience with real-time data streaming technologies like Apache Kafka or Spark Streaming
  • Good understanding of software engineering best practices, version control, testing, and CI/CD processes
  • Excellent communication and stakeholder management skills with the ability to lead technical discussions and mentor engineering teams


What Will Excite Us:


  • Experience designing enterprise-scale data platforms and modern cloud data architectures
  • Strong expertise in Databricks, Snowflake, or Delta Lake implementations
  • Experience building real-time data pipelines using Kafka, Spark Streaming, or similar technologies
  • Hands-on experience with DevOps and Infrastructure-as-Code tools such as Docker, Kubernetes, Terraform, GitHub Actions, Azure DevOps, or Jenkins
  • Experience optimizing data pipeline performance, scalability, reliability, and cost efficiency
  • Strong understanding of data governance, data quality, security, and performance optimization
  • Experience leading technical teams, conducting code reviews, and mentoring data engineers
  • Exposure to modern DataOps practices and automation frameworks
  • Ability to work across multiple client projects while ensuring high-quality delivery


What Will Excite You:


  • Opportunity to architect and build large-scale cloud-native data platforms for global clients
  • Work with modern technologies including Databricks, Snowflake, Kafka, Airflow, and leading cloud ecosystems
  • Lead technical initiatives while mentoring and growing high-performing engineering teams
  • Solve complex data engineering challenges involving large-scale data processing and real-time analytics
  • Collaborate with cross-functional teams in a fast-paced, innovation-driven environment
  • Competitive compensation, continuous learning opportunities, and significant career growth


Location: Ahmedabad (Work From Office)

See also

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