Key Responsibilities
ETL Design and Development
• Design, implement, and maintain ETL processes to extract, transform, and load data from diverse sources into data warehouses or other storage systems.
• Optimize ETL workflows for performance, reliability, and scalability.
• Build reusable ETL components and enforce data quality and observability across pipelines. Data Integration
• Develop and manage data integration solutions, integrating structured and unstructured data from multiple sources.
• Work with APIs, databases, and flat files to retrieve, process, and stage data.
• Ensure data lineage, cataloging, and metadata are properly maintained. Data Transformation
• Clean, transform, and standardize data to meet business and analytics requirements.
• Apply validation, enrichment, and aggregation techniques to produce reliable datasets.
• Implement error handling and data reconciliation mechanisms. Data Warehouse Development
• Support the design and development of schemas (star/snowflake) and dimensional models.
• Implement and manage database objects such as tables, views, stored procedures, indexes, and partitions.
• Collaborate with BI/Analytics teams to ensure models meet reporting and performance needs. Monitoring and Troubleshooting
• Monitor ETL processes for failures, inconsistencies, and SLA breaches; troubleshoot issues proactively.
• Implement alerting, retry, and recovery mechanisms; maintain runbooks and SOPs.
• Track pipeline health via dashboards and logs; conduct root cause analysis (RCA) and performance tuning. Mandatory Skills
• ETL Tools/Frameworks: Hands-on with at least one (e.g., Talend, Informatica, Pentaho, SSIS, dbt, Apache Airflow/Luigi/NiFi).
• SQL & Data Modeling: Strong SQL, dimensional modeling (star/snowflake),



query optimization.
• RDBMS: Experience with Oracle and PostgreSQL (DDL/DML, indexing, partitioning, performance tuning).
• Kafka: Practical experience with topics, producers/consumers, offsets, schema management, and cluster monitoring.
• Scripting: Python or Shell for automation, data parsing, and ETL orchestration.
• APIs & Files: Integration using REST APIs, JSON/CSV/Parquet, and file-based ingestion patterns.
• Monitoring & Observability: Experience with pipeline monitoring, logging, and alerting (e.g., Grafana/Prometheus/ELK).
• Version Control & CI/CD: Git and CI/CD for ETL deployments. Desirable Skills
• Cloud Data Platforms: AWS/Azure/GCP (e.g., S3/ADLS, Glue/Data Factory, Lambda/Functions).
• Streaming & Batch: Experience with Kafka Connect, ksqlDB, or Spark/Flink for streaming ETL.
• Orchestration: Airflow DAG design best practices; SLA management and backfills.
• Data Quality: Great Expectations / Deequ; data validation frameworks.
• Performance Tuning: SQL and pipeline performance tuning at scale.
• Security & Compliance: Row/column-level security, encryption at rest/in transit, data governance. Behavioral & Skilled Attributes
• Strong analytical and problem-solving abilities with a data-driven mindset.
• Ownership-oriented; able to work independently and in cross-functional teams.
• Clear and concise communication with stakeholders (engineering, BI, product).
• Detail-focused with strong documentation habits (runbooks, SOPs, design specs).
• Comfortable working in fast-paced environments with shifting priorities and SLAs. Nice-to-Have (Tools & Ecosystem)
• Experience with dbt, Snowflake/Redshift/BigQuery, Oracle GoldenGate, or AWS DMS.
• Exposure to data catalog tools and metadata management.

📌 Reporting and Data Migration lead (Bengaluru)
🏢 Comviva
📍 Bengaluru