Lead DataOps Engineer
4 weeks ago
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:
- Build the DataOps team and run day-to-day operations of the Azure Databricks Data & Analytics platform.
- Ensure data pipelines run smoothly and efficiently.
- Guarantee service availability and data availability as per SLA.
- Implement proactive monitoring and follow-up actions to ensure accuracy, timeliness, and completeness of data.
- Ensure adherence to security guidelines and audit control measures.
- Investigate, analyze, and resolve data/batch incidents within SLA.
- Conduct root cause analysis (RCA) and implement proactive preventive measures.
- Provide technical advice to the team and assist in issue resolution with strong competency in Cloud and Databricks.
- Provide on-call support and after-hours/weekend support as needed.
- Participate in Major Incident calls and lead the team for incident resolution.
- Fulfill service requests related to the Data Analytics platform.
- Plan and execute regular housekeeping, maintenance, and capacity management activities.
- Own and drive modern Data Operations.
- Develop and maintain operational-related SOPs and guidelines.
- 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
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