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About the role
Employment type- Contract basis Key Responsibilities Design, develop, and maintain scalable data pipelines using PySpark and distributed computing frameworks.Implement ETL processes and integrate data from structured and unstructured sources into cloud data warehouses.Work across Azure or AWS cloud ecosystems to deploy and manage big data workflows.Optimize performance of SQL queries and develop stored procedures for data transformation and analytics.Collaborate with Data Scientists, Analysts, and Business teams to ensure reliable data availability and quality.Maintain documentation and implement best practices for data architecture, governance, and security. Required Skills Programming: Proficient in PySpark, Python, and SQL, MongoDBCloud Platforms: Hands-on experience with Azure Data Factory, Databricks, or AWS Glue/Redshift.Data Engineering Tools: Familiarity with Apache Spark, Kafka, Airflow, or similar tools.Data Warehousing: Strong knowledge of designing and working with data warehouses like Snowflake, BigQuery, Synapse, or Redshift.Data Modeling: Experience in dimensional modeling, star/snowflake schema, and data lake architecture.CI/CD & Version Control: Exposure to Git, Terraform, or other DevOps tools is a plus. Preferred Qualifications Bachelor's or Master's in Computer Science, Engineering, or related field.Certifications in Azure/AWS are highly desirable.Knowledge of business intelligence tools (Power BI, Tableau) is a bonus. Employment type- Contract basis Key Responsibilities Design, develop, and maintain scalable data pipelines using PySpark and distributed computing frameworks.Implement ETL processes and integrate data from structured and unstructured sources into cloud data warehouses.Work across Azure or AWS cloud ecosystems to deploy and manage big data workflows.Optimize performance of SQL queries and develop stored procedures for data transformation and analytics.Collaborate with Data Scientists, Analysts, and Business teams to ensure reliable data availability and quality.Maintain documentation and implement best practices for data architecture, governance, and security. Required Skills Programming: Proficient in PySpark, Python, and SQL, MongoDBCloud Platforms: Hands-on experience with Azure Data Factory, Databricks, or AWS Glue/Redshift.Data Engineering Tools: Familiarity with Apache Spark, Kafka, Airflow, or similar tools.Data Warehousing: Strong knowledge of designing and working with data warehouses like Snowflake, BigQuery, Synapse, or Redshift.Data Modeling: Experience in dimensional modeling, star/snowflake schema, and data lake architecture.CI/CD & Version Control: Exposure to Git, Terraform, or other DevOps tools is a plus. Preferred Qualifications Bachelor's or Master's in Computer Science, Engineering, or related field.Certifications in Azure/AWS are highly desirable.Knowledge of business intelligence tools (Power BI, Tableau) is a bonus.
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