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Tier-1 brand, mid-level generalist data role and Bangalore metro increase candidate competition.
Core big-data and cloud engineering skills transfer across industries, but heavy tooling specifics raise sensitivity.
Explicit 5-8 years requirement plus extensive mandatory big-data, cloud and tooling skills increases strictness.
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Design, build, and implement robust data pipelines and infrastructure using big data and cloud technologies.
Develop data integration, transformation, and processing solutions leveraging tools like Spark, Kafka, Airflow, and AWS services.
Ensure efficient data processing and support actionable insights to drive client decision-making and business growth.
5-8 years of work experience in data engineering or related roles.
Proficient in Big Data technologies, AWS, SQL, Python/Scala, Spark, and related tools (S3, Glue, EMR, Lambda, Kinesis, Kafka, Airflow, DBT, Flink, Apache Iceberg, Datadog).
Bachelor's degree in Engineering (B.Tech, B.E) or equivalent (M.Tech, M.E, MCA).
Experience with CI/CD frameworks and code repositories like GitHub; Snowflake experience is a strong plus.
Experienced in designing scalable data platforms and pipelines using modern big data and cloud-native architectures.
Comfortable working with complex data ecosystems involving streaming, batch processing, orchestration, and monitoring tools.
Capable of implementing end-to-end data engineering solutions that integrate multiple technologies for business analytics impact.