Position Summary: The Senior Analytics Engineer architects, builds, and operates secure, scalable data pipelines and analytics integrations within a governed AWS cloud environment. This role carries direct accountability for data quality, privacy-preserving engineering, and compliance with HIPAA, SOC 2, GDPR, and CCPA. The individual serves as the technical authority on analytics engineering standards and partners with Security, Legal, and Compliance teams to ensure all data products meet enterprise governance requirements.

Deep hands-on expertise required across the following AWS service areas: Data Storage & Lake: S3, Lake Formation, Glue Data Catalog, DynamoDB Processing & ETL: Glue (PySpark), Lambda, Step Functions, EMR Analytics & Query: Athena, Redshift / Redshift Serverless, QuickSight Integration & Streaming: Kinesis, API Gateway, Transfer Family, AppFlow Security & Encryption: KMS, IAM, Secrets Manager, Macie, GuardDuty, CloudTrail Monitoring & Compliance: CloudWatch, AWS Config, X-Ray, Systems Manager Networking & Isolation: VPC, PrivateLink, AWS Clean Rooms

Responsibilities: Design data architectures compliant with HIPAA (PHI encryption, minimum necessary access, audit retention), GDPR/CCPA (DSAR automation, right-to-erasure, consent management), SOC 2 Type II (access reviews, change management, continuous monitoring), and PCI DSS where applicable. Implement data residency and sovereignty controls ensuring data remains within approved AWS Regions. Enforce data classification standards (Public, Internal, Confidential, Restricted) via Macie and Lake Formation LF-Tags. Implement automated data quality frameworks with freshness, completeness, and accuracy SLAs. Maintain data lineage documentation, data retention/purge policies via S3 Lifecycle Rules and DynamoDB TTL, and participate in Data Governance Council reviews and compliance audits. Implement least-privilege access models with quarterly reviews, IAM Access Analyzer scans, and encryption-at-rest/in-transit standards with KMS key policy management. Design masking, tokenization, and anonymization pipelines for non-production environments. Enforce IaC governance via CloudFormation/Terraform with security review gates and drift detection. Architect production-grade, fault-tolerant batch and real-time data pipelines within a compliance-governed AWS environment. Lead data modeling (dimensional, SCD, data vault) and build API/file-based integrations with encryption and audit logging at every point. Build CI/CD pipelines for data infrastructure with mandatory security scanning and approval gates. Conduct code reviews, mentor engineers, and produce technical documentation including ADRs, runbooks, and compliance evidence packages.

Job Requirements: Bachelor’s degree in Computer Science, Data Engineering, or related field; 7+ years in Analytics/Data Engineering. Expert SQL and Python (PySpark, Pandas, Boto3); deep AWS experience across the data, security, and governance stack. Demonstrated experience implementing governance frameworks and regulatory compliance controls (HIPAA, SOC 2, GDPR, CCPA) in production. Experience with IaC (CloudFormation, Terraform, CDK), CI/CD for data pipelines, and data security principles. AWS certifications (Data Analytics Specialty, Security Specialty, Solutions Architect Professional). Experience with data quality frameworks (Great Expectations, dbt, Monte Carlo), and regulated industries (healthcare, financial services) preferred.