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Mid-level data engineer in Bangalore with broad AWS/Spark requirements increases applicant competition.
Core AWS data platform and Spark expertise moderately limits transferability across industries.
Explicit 5–8 years, mandatory AWS experience and specific tech stack enforce strict filters.
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Design and implement scalable, secure, and cost-effective data platforms on AWS.
Lead development of complex ETL/ELT pipelines and data workflows ensuring data quality and governance.
Collaborate with cross-functional teams to define requirements and optimize data solutions for performance and cost-efficiency.
5 to 8 years of data engineering experience with at least 3 years hands-on AWS Cloud big data platform expertise.
Bachelor’s degree in Computer Science, Engineering, or related field.
Proficiency in Python, SQL, Spark, and AWS data services including Glue, S3, Redshift, Lambda, CloudWatch, and IAM.
Hybrid work mode in Bangalore with 3 mandatory in-office days.
Experienced in data architecture, data modeling, and warehousing with a strong grasp of best practices.
Skilled in DevOps practices with experience in CI/CD, monitoring, infrastructure-as-code (e.g., Terraform, CloudFormation).
Able to lead technical decisions, conduct code reviews, and collaborate effectively across data science, analytics, and business teams.