Senior Big Data Engineer

Responsibilities Design and build scalable data lakes and pipelines on AWS using cloud-native and automated solutions. Enable fast, federated analytics using Amazon Athena and Trino, with performance tuning for large-scale queries. Manage metadata, schemas, and discovery using AWS Glue Data Catalog. Implement fine-grained data access and governance using AWS Lake Formation, KMS encryption, and SSL. Build and operate data services on EKS (Kubernetes). Work with the Hadoop ecosystem (Spark, Hive, HDFS) using partitioning, bucketing, and columnar formats (Parquet, ORC). Troubleshoot and resolve complex big data issues across pipelines, clusters, and queries. Design, implement, and maintain CI/CD pipelines using Jenkins or similar tools. Monitor and observe pipelines and clusters using CloudWatch and Grafana. Prepare high-quality datasets for AI/ML use cases. Build, configure, and operate an MCP server for AI/ML integration. Collaborate in Scrum teams; proactively identify gaps and propose out-of-the-box, scalable solutions.

Qualifications Required:

8+ years of experience in Big Data / Data Engineering. Strong hands-on experience with AWS (S3, Glue Data Catalog, Lake Formation, Athena, EMR, EKS). Proven experience with Trino (or Presto) and optimizing query performance. Working knowledge of Kubernetes / EKS for data workloads. Strong SQL, Python, and shell scripting skills. Experience with CI/CD pipelines and Jenkins. Experience building and configuring MCP server for AI/ML integration. Ownership mindset problem solver, not a task executor.

Preferred:

AI/ML data pipeline exposure Cloud-native data modernization experience Candidates are required to be living in the MVD area at the time of the interview.