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Mid-level Data Engineer role with broad AWS/Spark requirements in Pune drives high competition.
Core skills like Spark, ETL, and AWS are highly transferable across industries, lowering background sensitivity.
Mandatory AWS big-data stack, Spark, ETL, BI tools and explicit 3-5 years experience make screening strict.
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Design, implement, and support analytical data infrastructure enabling ad-hoc access to large datasets with computing power.
Develop and maintain real-time data pipelines using AWS technologies such as Glue, Redshift/Spectrum, Kinesis, EMR, and Athena.
Collaborate with technology teams to build and operationalize advanced analytics algorithms, machine learning models, and improve reporting/analysis processes.
3-5+ years of industry experience in software development, data engineering, business intelligence, data science, or related field with experience handling large datasets.
Bachelor’s degree in Computer Science, Engineering, Mathematics, or related technical discipline.
Strong skills in data modeling, ETL development, data warehousing, and big data processing using Spark.
Experience using AWS big data technologies including Redshift, S3, EMR, and Spark.
Experienced in building and operating highly available distributed data extraction, ingestion, and processing systems.
Proficient in integrating business intelligence tools and leveraging data for statistical analysis, prediction, clustering, and machine learning.
Familiar with software engineering best practices covering agile lifecycle, coding standards, code reviews, source control, testing, and operations.