Big Data Engineer (Fulltime only)

Sr Dev – AWS Data Engineer with 12+ years of software development experience –

Architect and implement scalable batch and near-real-time data pipelines using Python, PySpark, Glue, EMR, Lambda, and Step Functions.

Define data storage, transformation, and access patterns across S3, Redshift, Athena, RDS, and DynamoDB.

Design event-driven and integration solutions using SNS, SQS, Kinesis, and APIs.

Establish standards for data quality, observability, monitoring, logging, and failure recovery.

Optimize data processing, storage, and query performance across AWS platforms.

Lead troubleshooting of production issues and drive root cause analysis and corrective actions.

Support cloud migration, data migration, and modernization initiatives.

Review solution designs, code quality, and production readiness across projects.

Collaborate with architects, platform teams, and business stakeholders to align technical solutions with business needs.

Drive best practices for CI/CD, deployment automation, and documentation. Required Skills and Qualifications - Solid IT background and experience.

Experience as an application developer for projects similar in scope and responsibility.

Advanced knowledge of AWS services and architecture.

Strong experience with Python object-oriented programming, PySpark, SQL, and ETL frameworks.

Deep experience with AWS services including Glue, EMR, Redshift, RDS, Athena, Lambda, Step Functions, SNS, SQS, S3, CloudWatch, and CloudTrail.

Strong understanding of enterprise data architecture, migration, and support models.

Experience with GitLab and Terraform and release/deployment practices. Preferred Skills

Experience with Kinesis, ECS, Batch, Beanstalk, and DynamoDB.

Exposure to infrastructure-as-code and reusable platform patterns.

Have a good understanding of performance engineering of code pipelines and near real time systems

Good understanding on Agents and MCP