Senior Data Engineer

Position Overview:

This position offers an opportunity to work in a collaborative environment where innovation and problem-solving are encouraged. The Data Engineer will play a key role in ensuring that high-quality, reliable, and scalable data solutions support business intelligence, analytics, and reporting needs.

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Key Responsibilities:

• Design, develop, and maintain data pipelines and ETL/ELT processes using Python and SQL
• Build and optimize dimensional models (fact tables, dimension tables, data marts) for analytics and reporting
• Implement data ingestion from databases, APIs, files, and real-time streams
• Develop data transformation logic to cleanse, validate, and enrich data
• Create and maintain documentation (data lineage, data dictionaries, pipeline specifications)
• Monitor and optimize pipeline performance for efficiency and reliability
• Collaborate with stakeholders to translate business requirements into technical solutions
• Implement automated data quality checks and validation rules
• Support migration projects from SQL Server to Aurora Postgres databases
• Build scalable, serverless data processing solutions with AWS services
• Develop Power BI reports and dashboards based on dimensional models
• Participate in data governance and ensure compliance with security and privacy requirements
• Troubleshoot and resolve data-related issues and provide ongoing support

Required Qualifications:

• Proven experience designing and implementing data pipelines for complex business needs
• Proficiency in Python (pandas, numpy, or similar data libraries)
• Strong SQL skills (complex queries, stored procedures, performance optimization)
• Experience with dimensional modeling (star schema, snowflake schema, SCDs)
• Hands-on experience with AWS data services (S3, Lambda, Glue, Athena, Step Functions)
• Strong background with SQL Server and PostgreSQL including data migration
• Experience with Snowflake for data warehousing and analytics
• Proficiency in Power BI for reporting and dashboards
• Solid understanding of ETL/ELT processes and integration patterns
• Experience in data quality validation, testing, and monitoring
• Ability to work with multiple data formats (JSON, CSV, Parquet, APIs)
• Knowledge of data governance, security, and compliance.

Preferred Qualifications:

• Experience in healthcare, government, or other regulated industries
• Familiarity with HIPAA, FedRAMP, or similar compliance frameworks
• Experience with real-time processing (Kinesis, EventBridge, or equivalent)
• Knowledge of Infrastructure as Code tools (CloudFormation, CDK, Terraform)
• Experience with metadata management and data cataloging tools
• Exposure to machine learning data preparation and advanced analytics concepts
• Familiarity with Git and CI/CD pipelines
• Background in Agile methodologies