Data ETL/Engineering

Key Responsibilities
Design, develop, and maintain robust ETL/ELT pipelines
Build scalable data ingestion frameworks (batch & real-time)
Integrate APIs, third-party data sources, and web scrapers
Develop and manage data warehouses and data lakes
Optimize database performance and query efficiency
Implement data validation, monitoring, and observability
Automate workflows and scheduling using orchestration tools
Collaborate with Analytics, Product, and Engineering teams
Ensure data security, governance, and compliance standards

Technical Requirements
Strong proficiency in Python and SQL
Experience building ETL pipelines from scratch
Hands-on with data warehouses (BigQuery / Redshift / Snowflake)
Experience with orchestration tools (Airflow / Prefect / Dagster)
Experience with cloud platforms (AWS / GCP / Azure)
Knowledge of data modeling (star schema, normalization)
Experience working with APIs and large datasets
Familiarity with Docker and CI/CD pipelines

Good to Have
Experience with streaming tools (Kafka / PubSub)
Knowledge of Spark or distributed computing
Experience in setting up data observability and monitoring
Exposure to ML pipelines