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Strong Tier-1 brand, mid-level generalist data role, broad skills and metro hybrid location increase competition.
Core data engineering skills are highly transferable across industries, so background sensitivity is low.
Explicit 5–8 years requirement plus mandatory AWS, Databricks and Spark experience makes screening strict.
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Engineer scalable cloud-based data solutions using AWS services, Databricks, Teradata Vantage, and CI/CD to optimize workflows and reduce manual intervention.
Design and implement enterprise architecture-aligned software solutions within an agile environment supporting advanced reporting and analytics.
Lead code reviews, manage production releases, and apply DevOps tools such as Github, Jenkins, Terraform, and Liquibase to streamline development and deployment.
Bachelor’s degree in Engineering, Computer Science, or related discipline.
5 to 8 years of experience in application program development or equivalent.
Hands-on experience with AWS services including Lambda, Step Functions, CloudTrail, CloudWatch, SNS, SQS, S3, VPC, EC2, RDS, and IAM.
Proficiency in Python, Databricks, SQL, Unix, SPARK, real-time analytic frameworks, and standard SDLC processes.
Experienced in business intelligence or analytic development on large-scale projects with ability to handle large datasets and complex troubleshooting.
Demonstrates ownership and technical excellence within a high-performing, agile, team-oriented environment.
Skilled in communicating design and development processes clearly to both technical teams and clients.