01Overview
Design, build, and maintain scalable ETL/ELT pipelines for batch and real-time data ingestion and transformation.Develop and optimize data lake and data warehouse architectures (e.g., Snowflake, BigQuery, Redshift).Work with cloud platforms GCP, Azure to manage data infrastructure.GCP as mandatory skillsCollaborate with analytics and product teams to understand data needs and deliver solutions.Ensure data quality, reliability, security, and compliance across all data systems.Mentor junior data engineers and contribute to best practices and code reviews.Monitor and troubleshoot data pipeline performance and resolve data-related issues.Automate data validation, monitoring, and alerting processes.8+ years of experience in data engineering or software engineering with a data focus.Proficient in SQL and at least one programming language (e.g., Python, Scala, Java).Experience with modern data warehousing tools (e.g., Snowflake, Redshift, BigQuery).Strong understanding of data modeling, data lakes, and ETL/ELT design.Hands-on experience with orchestration tools like Airflow, dbt, or similar.Solid experience with cloud data platforms (AWS/GCP/Azure).Familiarity with CI/CD pipelines, containerization (Docker/Kubernetes), and version control (Git).Experience working in a DevOps or DataOps environment.Knowledge of data governance, lineage, and cataloging tools (e.g., Collibra, Alation).Familiarity with streaming technologies (Kafka, Spark Streaming, Flink).Experience supporting machine learning workflows and data science initiatives. .
