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Lead DataOps Engineer

2 months ago

Pune, India RS Consulting Full time

Job Title: Lead DataOps Engineer

Location: Pune, India

Experience: 10+ Years


Job Description: As a DataOps Engineer, you will be responsible for managing data operations in a Cloud Data Lakehouse environment. You will lead the DataOps team and ensure the smooth functioning of the Azure Databricks Data & Analytics platform.


Key Responsibilities:

  1. Build the DataOps team and run day-to-day operations of the Azure Databricks Data & Analytics platform.
  2. Ensure data pipelines run smoothly and efficiently.
  3. Guarantee service availability and data availability as per SLA.
  4. Implement proactive monitoring and follow-up actions to ensure accuracy, timeliness, and completeness of data.
  5. Ensure adherence to security guidelines and audit control measures.
  6. Investigate, analyze, and resolve data/batch incidents within SLA.
  7. Conduct root cause analysis (RCA) and implement proactive preventive measures.
  8. Provide technical advice to the team and assist in issue resolution with strong competency in Cloud and Databricks.
  9. Provide on-call support and after-hours/weekend support as needed.
  10. Participate in Major Incident calls and lead the team for incident resolution.
  11. Fulfill service requests related to the Data Analytics platform.
  12. Plan and execute regular housekeeping, maintenance, and capacity management activities.
  13. Own and drive modern Data Operations.
  14. Develop and maintain operational-related SOPs and guidelines.
  15. Collaborate with other IT divisions and relevant vendors to participate in Group IT initiatives.


Qualifications:

  • Minimum 10 years of experience in the data analytics field.
  • At least 6 years of experience in running operations and support in a Cloud Data Lakehouse environment.
  • Proficiency in Azure Databricks.
  • Strong experience in building and optimizing data pipelines and architectures.
  • Excellent programming skills in Scala or Python.
  • Ability to troubleshoot and optimize complex queries on the Spark platform.
  • Knowledge of data access and storage techniques for both structured and unstructured data.
  • Experience with DevOps tools and environments.


Technical / Professional Skills:

  • Azure Databricks
  • Python / Scala / Java
  • HIVE / HBase / Impala / Parquet
  • Sqoop, Kafka, Flume
  • SQL and RDBMS
  • Airflow
  • Jenkins / Bamboo
  • Github / Bitbucket
  • Nexus