Data Engineer

Key Responsibilities

• Design, develop, and maintain scalable data platform solutions across AWS and hybrid/on-premises environments.

• Build, optimize, and support production-grade data pipelines using Python, PySpark, SQL, and cloud-native technologies.

• Implement and maintain ETL/ELT workflows, Data Lake/Lakehouse architectures, metadata management, search platforms, and AI services.

• Develop and maintain CI/CD pipelines, automated testing frameworks, deployment workflows, and infrastructure automation.

• Implement, integrate, and support AWS services and technologies such as OpenSearch, Amazon Bedrock, AgentCore, MCP, and related platform components.

• Monitor and optimize platform performance, reliability, security, observability, and cost efficiency.

• Troubleshoot production incidents, perform root-cause analysis, and ensure platform stability and operational excellence.

• Collaborate with data engineering, infrastructure, security, and application teams to drive platform modernization and continuous improvement.

Mandatory Requirements

• 3–5+ years of hands-on experience building and supporting production-grade data pipelines using SQL, Python, and cloud technologies.

• Practical experience with AWS and/or hybrid cloud environments.

• Strong Linux/Unix administration, shell scripting, troubleshooting, and production support capabilities.

• Solid understanding of data engineering principles, ETL/ELT processes, and distributed data processing.

Technical Skills

• Programming & Data Processing: Python, PySpark, SQL, Apache Spark

• AWS & Data Platforms: AWS Glue, EMR, S3, Redshift, Lambda

• Data Engineering & Streaming: Airflow, dbt, Kafka/MSK, Apache Iceberg, Hive, Trino, Presto

• Search & AI Platforms: OpenSearch, Amazon Bedrock, AgentCore, MCP

• DevOps & Automation: Git, CI/CD pipelines, Infrastructure as Code (IaC), automated testing, deployment automation

• Monitoring & Operations: Datadog, CloudWatch, Grafana, Prometheus, Linux/Unix administration

Preferred Qualifications

• Experience with enterprise Data Lake and Lakehouse platforms.

• Knowledge of streaming and event-driven architectures.

• Hands-on experience with OpenSearch administration, performance optimization, and tuning.

• Familiarity with monitoring, observability, and production support tools.

• Understanding of data governance, security, access controls, and Personally Identifiable Information (PII) protection.

• Experience in banking, insurance, or other financial services environments.
  

  Ankita

  EA License Number: 23C2060 Registration ID is R22109715

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