Lead Database / Data Engineer- Immediate Joiner (Karnataka)

Are you a PostgreSQL expert who thrives on optimizing complex queries, managing massive retail data pipelines, and architecting robust Lakehouse environments? Taglynk is looking for a seasoned Lead Database & Data Engineer to join our team! If you have a passion for zero-downtime deployments, high-performance SQL, and scalable data automation, we want to hear from you. Role Overview Position: Lead Database / Data Engineer Experience: 7–11 years of hands-on experience Core Tech: PostgreSQL, Airflow, GCP, Delta Lake / Iceberg ️ Key Responsibilities Database Development Production-Grade SQL: Write complex queries, stored procedures, functions, views, and triggers for high-velocity microservices with a strong focus on correctness and performance. Schema Design: Design and implement database schemas (tables, indexes, partitions) under the guidance of our Database Architect. Performance Tuning: Tune slow queries using EXPLAIN ANALYZE, fixing index misuse, missing partitions, and vacuum issues in PostgreSQL. Migrations: Safely implement and test backward-compatible schema migrations for zero-downtime deployments. Security: Maintain database security using basic RBAC, access controls, and encryption standards. ETL & Data Pipelines Pipeline Support: Support Airflow pipelines processing retail data (1GB–50GB daily), managing ingestion, cleansing, and transformation across DBs and Lakehouse zones. DAG Management: Monitor and operate Airflow/Prefect DAGs, troubleshoot failures, fix dependencies, and improve retry logic. Data Quality: Implement strict data quality checks (null checks, referential integrity, range validation) within pipeline stages. Schema Evolution: Support schema evolution in Delta Lake / Apache Iceberg datasets, handling partition changes and backfills. Cloud, Tooling & Automation Cloud Infrastructure: Work with managed cloud databases on GCP (Cloud SQL, BigQuery) for day-to-day operations and query optimization. Observability: Set up query duration dashboards, replication health alerts, and pipeline SLA monitoring via GCP/DataDog. Scripting: Write Python scripts for data automation, validation pipelines, and ad-hoc data investigations. Collaboration & Documentation Partner with ML, Analytics, and Product Engineers to understand data access patterns and support feature extraction queries. Participate in sprint planning, estimate database work accurately, and flag technical risks early. Propose solutions and raise design questions to the Database Architect before implementation. Document table structures, pipeline logic, and system runbooks. Must-Have Qualifications 7–11 years of hands-on database development and data engineering experience. Robust SQL & PostgreSQL expertise: Deep experience with stored procedures, triggers, views, indexes, partitioning, and query tuning. Lakehouse Ecosystems: Proven contributor experience in a Lakehouse environment using Delta Lake or Apache Iceberg . Apply on Kit Job: kitjob.in/job/4mmhss