Description

• 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 skills • Collaborate 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. • 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 initiativespporting machine learning workflows and data science initiativesc

Key Skills

Education

Bachelor's degree