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Remote role, metro Gurgaon, generalist Data Engineer title and recognizable financial brand increase applicant competition.
Core data engineering skills (AWS, Spark, ETL) are highly transferable across industries.
Explicit 7–12 years and mandatory AWS, Spark, Kafka, Python and data platform skills enforce strict filters.
Design, develop, and maintain scalable, large-scale data pipelines and infrastructure on AWS cloud platform.
Optimize performance, scalability, and reliability of data processing jobs using technologies like Spark and Kafka.
Lead and mentor junior data engineers; collaborate with data scientists, analysts, DevOps, and business stakeholders for advanced analytics and reporting tools.
7 to 12 years of experience as a Data Engineer or similar role with strong AWS cloud focus.
Bachelor’s degree in Computer Science, Engineering, or related field; Master’s preferred.
Hands-on experience with AWS services: S3, DMS, Lambda, EMR, Glue, Redshift, RDS, Athena, Kinesis.
Proficiency in Python, PySpark, SQL/PLSQL and knowledge of data warehousing and data modeling required.
Experienced in large-scale cloud data engineering projects, particularly AWS-based data lake and warehouse deployments.
Comfortable driving cloud-native data infrastructure, including CI/CD pipelines and data observability.
Capable of leading teams and managing cross-functional collaborations for enterprise data solutions.