Data Engineer – AWS / PySpark / ETL

**About The Role** We are looking for an experienced Data Engineer with strong expertise in AWS, PySpark, and ETL development to join our growing data engineering team. The ideal candidate should have hands\-on experience in building scalable data pipelines, processing large datasets, and developing reporting solutions using Tableau or Power BI. **Key Responsibilities** * Design, develop, and maintain scalable ETL/data pipeline solutions using PySpark and AWS services. * Build and optimize batch and real\-time data processing workflows. * Develop data integration solutions for structured and unstructured data sources. * Work closely with business stakeholders and analytics teams to gather requirements and deliver data solutions. * Create dashboards and reports using Tableau or Power BI for business insights and reporting. * Ensure data quality, integrity, security, and governance across systems. * Optimize data workflows and troubleshoot performance bottlenecks. * Participate in code reviews, testing, deployment, and production support activities. * Implement best practices for data engineering, automation, and monitoring **Required Skills** * 6\+ years of experience in Data Engineering and ETL development. * Strong hands\-on experience with AWS services such as S3, * Glue, EMR, Lambda, Redshift, Athena, or EC2\. * Expertise in PySpark and distributed data processing. * Strong SQL skills and experience with relational databases. * Experience with Tableau or Power BI dashboard/report development. * Good understanding of data warehousing concepts and big data technologies. * Familiarity with version control tools such as Git. * Strong analytical, debugging, and problem\-solving skills. **Preferred Skills** * Experience with Airflow, Kafka, Databricks, or Snowflake is a plus. * Knowledge of Python scripting and cloud\-based data architecture. * Experience working in Agile/Scrum environments. * AWS Certification is an added advantage.