Etl/elt specialist

You are a hands-on Data Engineer responsible for designing, building, and maintaining scalable data pipelines and data platforms. Your role involves ingesting, transforming, and serving data reliably for analytics, reporting, and downstream applications, collaborating closely with backend engineers, analysts, and data scientists. This position is ideal for you if you enjoy building robust data systems, working with large datasets, and writing clean, production-grade code. - Build and maintain reliable ETL/ELT pipelines for batch and near-real-time data processing. - Ingest data from multiple sources such as databases, APIs, event streams, and files. - Transform raw data into clean, analytics-ready datasets. - Optimize pipelines for performance, scalability, and cost. - Design and manage data models in data warehouses or data lakes. - Work with SQL and No SQL databases and modern data warehouses. - Implement partitioning, indexing, and efficient query patterns. - Maintain documentation for schemas, pipelines, and transformations. - Build data solutions on cloud platforms, with preference for AWS. - Use services such as S3, Redshift, Athena, Glue, EMR, Lambda, Kinesis, or equivalents. - Work with orchestration tools like Airflow or similar schedulers. - Use version control, CI/CD, and Infrastructure-as-Code where applicable. - Implement data validation, monitoring, and alerting for pipelines. - Troubleshoot data issues and ensure pipeline reliability. - Collaborate with stakeholders to resolve data discrepancies. Qualifications Required: - 4 to 6+ years of experience as a Data Engineer / Data Developer. - Strong programming skills in Python. - Excellent knowledge of SQL and relational data modeling. - Experience building ETL/ELT pipelines in production. - Hands-on experience with cloud-based data platforms, with preference for AWS. - Understanding of data warehousing concepts and best practices. Nice to have: - Experience with Spark, Kafka, dbt, or Flink. - Familiarity with orchestration tools like Airflow. - Experience with streaming or event-driven data pipelines. - Exposure to data quality or observability tools. - Experience working with large-scale or high-volume datasets. The company is based in Chennai (Velachery) and follows a Work from Office model. Their online presence can be found on all social media platforms under the name "Ai (we Health)." You are a hands-on Data Engineer responsible for designing, building, and maintaining scalable data pipelines and data platforms. Your role involves ingesting, transforming, and serving data reliably for analytics, reporting, and downstream applications, collaborating closely with backend engineers, analysts, and data scientists. This position is ideal for you if you enjoy building robust data systems, working with large datasets, and writing clean, production-grade code. - Build and maintain reliable ETL/ELT pipelines for batch and near-real-time data processing. - Ingest data from multiple sources such as databases, APIs, event streams, and files. - Transform raw data into clean, analytics-ready datasets. - Optimize pipelines for performance, scalability, and cost. - Design and manage data models in data warehouses or data lakes. - Work with SQL and No SQL databases and modern data warehouses. - Implement partitioning, indexing, and efficient query patterns. - Maintain documentation for schemas, pipelines, and transformations. - Build data solutions on cloud platforms, with preference for AWS. - Use services such as S3, Redshift, Athena, Glue, EMR, Lambda, Kinesis, or equivalents. - Work with orchestration tools like Airflow or similar schedulers. - Use version control, CI/CD, and Infrastructure-as-Code where applicable. - Implement data validation, monitoring, and alerting for pipelines. - Troubleshoot data issues and ensure pipeline reliability. - Collaborate with stakeholders to resolve data discrepancies. Qualifications Required: - 4 to 6+ years of experience as a Data Engineer / Data Developer. - Strong programming skills in Python. - Excellent knowledge of SQL and relational data modeling. - Experience building ETL/ELT pipelines in production. - Hands-on experience with cloud-based data platforms, with preference for AWS. - Understanding of data warehousing concepts and best practices. Nice to have: - Experience with Spark, Kafka, dbt, or Flink. - Familiarity with orchestration tools like Airflow. - Experience with streaming or event-driven data pipelines. - Exposure to data quality or observability tools. - Experience working with large-scale or high-volume datasets. The company is based in Chennai (Velachery) and follows a Work from Office model. Their online presence can be found on all social media platforms under the name "Ai (we Health)."