SENIOR DATA ENGINEER - Azure DatabricksHappiest Minds Technologiesfull-timeRequired skillsPythonAzurecross-functionaldata modelsdata scienceDatabricksDevOpsETLRoot Cause AnalysisSQLversion controlAbout the role Happiest Minds Technologies Website: happiestminds.com Job details: Key Responsibilities: Willingness to work in second shift to support global stakeholders and business operations (CST (US)). Actively support BAU operations (L2 & L3) including incident triage, root cause analysis, bug fixes, data issue resolution, and performance tuning. Support BAU operations including incident triage, root cause analysis, bug fixes, and performance tuning. Build and maintain documentation, runbooks, and operational playbooks for pipelines and workflows. Enable observability through logging, lineage capture, and monitoring frameworks. Contribute to reusable frameworks, accelerators, and standardization of development practices. Work with downstream consumers (BI, analytics, data science) to optimize data availability and usability. Design, build, and maintain scalable data pipelines and workflows on modern data platforms (primarily Databricks and Azure stack). Implement and operationalize DataOps practices including monitoring, and alerting for data pipelines. Translate business/data requirements into efficient data models, transformations, and reusable components. Own ingestion, transformation, and curation layers (bronze/silver/gold) ensuring data quality, consistency, and performance. Collaborate with architects, SMEs, and cross-functional teams (platform, BI, and support) for seamless delivery and handoffs. Skills & Experience: 6?10 years of experience in data engineering and pipeline development. Strong hands-on expertise in Databricks (PySpark, Delta Lake, Workflows, notebooks). Proficiency in Python, SQL, and distributed data processing frameworks. Experience with Azure data services such as ADF, ADLS, Azure DevOps, and integration patterns. Hands-on experience in building and maintaining ETL/ELT pipelines at scale. Nice to have: CI/CD, version control, testing, and monitoring knowledge Familiarity with data quality frameworks, logging, and observability tools. Working knowledge of data governance concepts (catalog, lineage, access control). Experience supporting production environments with SLAs and incident management. Click on Apply to know more. This page is fully interactive when JavaScript is enabled. Please enable JavaScript to apply or browse related roles.