Bengaluru, Karnataka
Job Summary

A Senior Data Engineer (ETL) designs, builds, and optimizes scalable data pipelines to transform raw data into analytics-ready datasets. They own the architecture of the extraction, transformation, and loading processes, ensuring data quality, reliability, and optimal performance across enterprise data lakes and warehouses.

Key Responsibilities
Pipeline Development: Design and build complex, high-throughput ETL/ELT pipelines to ingest structured and unstructured data from diverse sources.
Data Architecture: Structure scalable data models, data warehouses (e.g., Snowflake, BigQuery, Redshift), and data lakes to support advanced analytics and reporting.
Performance Tuning: Optimize SQL queries, data indexing, partitioning, and cluster configurations to reduce compute costs and pipeline latency.
Data Quality & Governance: Implement automated testing, data validation frameworks, and data lineage tracking to guarantee data integrity and compliance.
CI/CD & Automation: Automate deployment workflows using CI/CD tools (e.g., GitHub Actions, Jenkins) and orchestrate pipelines using scheduling tools (e.g., Airflow, Prefect).




Skill Requirements
Experience: 7+ years of dedicated data engineering experience, with a proven track record of architecting production-grade ETL pipelines.
Programming Languages: Advanced proficiency in Python , Scala , or Java, alongside expert-level SQL optimization skills.
Big Data Frameworks: Hands-on experience with distributed computing tools such as Apache Spark , PySpark, Databricks, or Hadoop.
Cloud Infrastructure: Deep familiarity with cloud data ecosystems on AWS , Azure , or GCP .
Orchestration Tools: Robust experience managing complex workflows with Apache Airflow , Dagster, or similar orchestration engines
Other Requirements
1.Relevant certifications in Azure Data Factory, Azure Databricks, SQL, Oracle, or Python would be a plus.
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📌 Azure Senior Data Lead (India)
🏢 HCLTech
📍 India