Sr. Data Integration Engineer

ROLE AND RESPONSIBILITIES:

• Design and develop resilient batch and event-driven data pipelines using Python, AWS Glue, and appropriate AWS managed services.
• Build AWS Glue jobs, crawlers, workflows, triggers, and Data Catalog integrations to discover, transform, govern, and publish datasets.
• Ingest and process structured and semi-structured data from files, APIs, databases, and streaming or messaging sources, with particular expertise in JSON and NDJSON formats.
• Develop efficient Python components for parsing, schema validation, normalization, enrichment, deduplication, aggregation, and data quality checks.
• Use AWS services such as Amazon S3, AWS Lambda, Amazon EventBridge, AWS Step Functions, Amazon SQS, Amazon SNS, Amazon Kinesis, Amazon Athena, Amazon Redshift, AWS Lake Formation, AWS Secrets Manager, AWS KMS, Amazon CloudWatch, and AWS IAM as solution needs dictate.
• Create automated unit, integration, regression, and data reconciliation tests; embed data quality controls throughout the pipeline lifecycle.
• Implement operational monitoring, logging, alerting, traceability, restartability, error handling, and recovery mechanisms for production pipelines.
• Apply security and privacy requirements through least-privilege access, encryption, secure secret management, audit logging, and appropriate handling of sensitive data.
• Automate infrastructure and deployment processes using infrastructure as code and CI/CD practices.
• Optimize pipeline performance, reliability, scalability, and cost through profiling, tuning, service selection, and ongoing operational analysis.
• Investigate and resolve performance issues, failed jobs, and production incidents; document root causes and preventive actions.
• Create and maintain technical documentation, including source-to-target mappings, pipeline designs, data contracts, runbooks, lineage, test evidence, and operational procedures.
• Analyze and organize requirements into stories under epics, generate acceptance criteria, lead refinement sessions and work with Product Owners on prioritization.
• Work with external teams on timelines and raise risks appropriately.
• Maintain continuous communication with the customer, project SMEs, and key stakeholders to collect and document business requirements in support of their vision.
• Review test scenarios and work with team to include any missed impact points.
• Understand project delivery mechanisms and ensure owned stories/epics are tracked to closure.
• Track customer requirements from inception through delivery.
• Assist with user acceptance testing (UAT).
• Analyze data to understand business problems and opportunities.
• Identify and evaluate potential risks and impacts of proposed solutions.
• Provide ongoing support and maintenance for implemented solutions.
• Assist the product owner and development team to achieve customer satisfaction.

REQUIRED EXPERIENCE:

• 7+ years of relevant experience
• Strong Python development skills, including modular design, testing, debugging, packaging, dependency management, and performance optimization.
• Hands-on experience developing data pipeline solutions with AWS Glue and integrating Glue with Amazon S3 and the AWS Glue Data Catalog.
• Practical experience with multiple AWS data, integration, security, and monitoring services used to deliver end-to-end data pipelines.
• Demonstrated experience ingesting, parsing, validating, transforming, and troubleshooting JSON and NDJSON, including nested structures, malformed records, schema drift, and large-file processing.
• Experience with data modeling, schema design, data partitioning, metadata, lineage, and data quality practices.
• Experience using Git-based version control, automated testing, CI/CD pipelines, and infrastructure-as-code approaches.
• Excellent analytical, problem-solving, documentation, and communication skills, with a proactive and customer-focused approach.
• Exhibit strong verbal and written communication skills, attention to detail, and the ability to follow up in a timely manner.
• Have experience creating detailed reports and presenting information to both technical and non-technical audiences.
• Possess expertise in using JIRA and Confluence for managing requirements.
• Must be able to obtain and maintain a Public Trust clearance.
• Must have lived in the United States 3 out of the past 5 years.

PREFERRED EXPERIENCE:

• SAFe Agile Certification
• AWS certification relevant to data engineering, architecture, or development.
• Experience in healthcare IT and understanding of regulatory requirements such as HIPAA.
• Experience designing source-to-target mappings, canonical data models, and data integration patterns across heterogeneous data providers.
• Experience partnering with Data Quality and Data Governance teams to establish data quality metrics, validation rules, profiling processes, and remediation workflows.
• Experience managing data delivery requirements, service level agreements (SLAs), and operational readiness processes.
• Experience and/or knowledge of CMS programs, processes, and standards.
• Experience with Apache Spark or PySpark, Parquet, Avro, Iceberg, or other distributed processing and open table or columnar storage technologies.

EDUCATION AND CERTIFICATIONS:

• Bachelor's degree