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Remote mid-level data-engineer in Gurgaon with common AWS/Spark skills and known employer increases candidate competition.
Core data engineering and AWS skills are highly transferable across industries, yielding low background sensitivity.
Explicit 5–7 years plus mandatory AWS, PySpark, Kafka and data-modeling skills raise shortlisting strictness.
Design, develop, and maintain scalable large-scale data pipelines and infrastructure on AWS cloud platform.
Optimize data processing jobs for performance, scalability, and reliability using tools like Spark and Kafka.
Lead and mentor junior data engineers, collaborate with DevOps and cross-functional teams to deliver technology solutions supporting advanced analytics and business objectives.
5 to 7 years of experience as a Data Engineer or similar role with strong focus on AWS cloud.
Bachelor’s degree in Computer Science, Engineering, or related field (Master’s preferred).
Hands-on experience with AWS services including S3, DMS, Lambda, EMR, Glue, Redshift, RDS (Postgres), Athena, and Kinesis.
Proficiency in Python, PySpark, SQL/PLSQL for ETL and data pipeline implementation.
Experienced in cloud-based data architecture, specifically AWS solutions for data lakes, EDW, and analytics.
Skilled in applying DevOps practices like CI/CD in data engineering environments and implementing data observability.
Strong leadership skills with experience mentoring engineers and collaborating across business and technical teams.