Description

Key Skills: SQL, Python, Spark, Airflow, dbt, AWS, GCP, Azure, ETL, Data Pipelines

Good to Have Skills: Scala, Java, Dagster, Luigi, Flink, Hadoop, Redshift, BigQuery, Snowflake, Databricks, dimensional modeling, normalization, star/snowflake schemas, batch and streaming architectures, data warehousing, data lake, lakehouse concepts, file formats (Parquet, Avro, ORC), Git, CI/CD, testing, modularity, documentation, Terraform, Docker, Kubernetes, data quality, observability, monitoring, data governance, lineage, privacy/compliance.

Roles & Responsibilities:

• Design, build, and optimize scalable data pipelines and data platforms for enterprise-level operations.
• Collaborate with cross-functional teams to deliver reliable, high-quality data solutions while ensuring performance excellence.
• Implement ETL/ELT frameworks using distributed processing technologies to handle large-scale data operations.
• Develop and maintain data pipeline tools using Airflow, dbt, Dagster, or Luigi for automated workflows.
• Work with cloud-based data services on AWS, GCP, or Azure platforms for optimal data management.
• Ensure data governance, observability, and monitoring standards are maintained across all data processes.
• Translate ambiguous business requirements into reliable and efficient data pipeline solutions for stakeholders.
• Implement version control, CI/CD practices, and infrastructure-as-code for maintaining code quality and deployment processes.

Experience Required: 2 years

Key Skills

Education

Any Graduate