Data Engineer

As a skilled Data Engineer with 5-8 years of experience, you will be responsible for designing, building, and maintaining scalable data pipelines and infrastructure using Python and SQL. Your role will involve working closely with data analysts, data scientists, and cross-functional teams to ensure reliable data flow and optimized performance across systems. Key Responsibilities: - Design, develop, and maintain scalable ETL/ELT data pipelines. - Write complex, optimized SQL queries for large-scale datasets. - Build and maintain data warehouses and data lakes. - Ensure data quality, integrity, and security across systems. - Optimize database performance and troubleshoot data-related issues. - Work with cloud platforms (AWS/GCP/Azure) for data processing and storage. - Implement data models to support analytics and reporting. - Automate workflows using orchestration tools. - Collaborate with stakeholders to gather and translate business requirements into technical solutions. Required Skills & Qualifications: - Strong proficiency in Python (Pandas, NumPy, PySpark preferred). - Advanced SQL skills (complex joins, CTEs, window functions, query optimization). - Experience with relational databases (PostgreSQL, MySQL, SQL Server). - Experience with data warehousing solutions (Snowflake, Redshift, Big Query). - Hands-on experience with ETL tools (Airflow, dbt, Talend, etc.). - Knowledge of data modeling (star schema, snowflake schema). - Familiarity with big data tools (Spark, Hadoop) is a plus. - Experience with version control (Git). - Understanding of CI/CD pipelines. Preferred Cloud & Tools: - AWS (S3, Glue, Redshift, Lambda) - GCP (Big Query, Dataflow) - Azure Data Factory - Docker & Kubernetes (nice to have) Soft Skills: - Strong analytical and problem-solving skills. - Excellent communication and stakeholder management. - Ability to work independently and in a team. - Attention to detail and commitment to data accuracy. Education: - Bachelor's or master's degree in computer science, Engineering, Information Systems, or related field. Good to Have: - Experience with real-time streaming (Kafka). - Exposure to data governance and compliance frameworks. - Experience in Agile/Scrum environments. As a skilled Data Engineer with 5-8 years of experience, you will be responsible for designing, building, and maintaining scalable data pipelines and infrastructure using Python and SQL. Your role will involve working closely with data analysts, data scientists, and cross-functional teams to ensure reliable data flow and optimized performance across systems. Key Responsibilities: - Design, develop, and maintain scalable ETL/ELT data pipelines. - Write complex, optimized SQL queries for large-scale datasets. - Build and maintain data warehouses and data lakes. - Ensure data quality, integrity, and security across systems. - Optimize database performance and troubleshoot data-related issues. - Work with cloud platforms (AWS/GCP/Azure) for data processing and storage. - Implement data models to support analytics and reporting. - Automate workflows using orchestration tools. - Collaborate with stakeholders to gather and translate business requirements into technical solutions. Required Skills & Qualifications: - Strong proficiency in Python (Pandas, NumPy, PySpark preferred). - Advanced SQL skills (complex joins, CTEs, window functions, query optimization). - Experience with relational databases (PostgreSQL, MySQL, SQL Server). - Experience with data warehousing solutions (Snowflake, Redshift, Big Query). - Hands-on experience with ETL tools (Airflow, dbt, Talend, etc.). - Knowledge of data modeling (star schema, snowflake schema). - Familiarity with big data tools (Spark, Hadoop) is a plus. - Experience with version control (Git). - Understanding of CI/CD pipelines. Preferred Cloud & Tools: - AWS (S3, Glue, Redshift, Lambda) - GCP (Big Query, Dataflow) - Azure Data Factory - Docker & Kubernetes (nice to have) Soft Skills: - Strong analytical and problem-solving skills. - Excellent communication and stakeholder management. - Ability to work independently and in a team. - Attention to detail and commitment to data accuracy. Education: - Bachelor's or master's degree in computer science, Engineering, Information Systems, or related field. Good to Have: - Experience with real-time streaming (Kafka). - Exposure to data governance and compliance frameworks. - Experience in Agile/Scrum environments.