AWS + Pyspark Data Engineer ( Gurugram)

Job Overview Role: Senior Data Engineer Location: Gurugram, Haryana Experience Required: 4 to 8 Years Primary Tech Stack: AWS, PySpark, Advanced SQL Role Overview We are looking for a dynamic and results-driven Data Engineer with strong expertise in AWS, PySpark, and SQL to join our growing technology team in Gurugram. In this role, you will design, build, and optimize large-scale data pipelines, data warehouses, and modern cloud analytics platforms to handle high-volume data workloads. Key Responsibilities Pipeline Development: Design, develop, test, and maintain robust ETL/ELT data pipelines using PySpark and cloud-native services. Cloud & Big Data Management: Build, monitor, and optimize scalable data ingestion, transformation, and processing workflows on AWS (e.g., S3, Glue, EMR, Athena, Redshift, Lambda). SQL Optimization: Write complex SQL queries, perform query tuning, and manage database operations to ensure high performance and low latency. Data Modeling & Architecture: Collaborate with cross-functional teams to build data models, schema designs, and data marts supporting analytical reporting. Performance Tuning: Troubleshoot and resolve production performance bottlenecks in distributed data processing jobs. Collaboration: Work closely with Data Scientists, Business Analysts, and DevOps teams to align data platform infrastructure with business requirements. Best Practices: Ensure data quality, security, governance, and CI/CD automation standards are implemented across all deliverables. Required Qualifications & Skills Experience: 4 to 8 years of hands-on experience in Data Engineering, Big Data, or Business Intelligence roles. Programming Languages: Expert-level proficiency in Python and PySpark. Cloud Ecosystem: Strong production experience working with AWS cloud services (S3, Glue, EMR, Athena, Redshift, etc.). Database & Querying: Strong command over SQL programming, performance tuning, and database design principles. Big Data Frameworks: Familiarity with distributed computing principles and the Apache Spark ecosystem. Tools & Version Control: Experience with orchestration tools (e.g., Apache Airflow), containerization, and version control systems (Git). Education: Bachelors or Masters degree in Computer Science, Information Technology, Engineering, or a related quantitative field. Preferred / Good-to-Have Skills Exposure to modern data lakehouse platforms like Databricks or Snowflake. Experience working in fast-paced FinTech or Banking domains. Familiarity with CI/CD deployment models and infrastructure-as-code concepts. .