DATA ENGINEER

Key Responsibilities/ Accountabilities: Listing of key responsibilities / major activities necessary to fulfill the position’s purpose. If possible, please include the percentage of time spent on each key responsibility. Advanced Data Engineering and Solution Design (80%) • Architect and implement scalable data pipelines to process and integrate structured and unstructured data. • Design end-to-end data solutions, including Data Lake, Data Warehouse, and Data Mart, to support analytics and operational systems. • Leverage UDP framework to consolidate data pipelines across healthcare domains. • Support the integration of new data domains through standardized ingestion and transformation frameworks. • Collaborate with stakeholders to translate business requirements into scalable, high-performing data architectures. • Integrate and optimize data access across distributed systems using data federation and virtualization tools • Develop reusable data assets to support self-service analytics across programs and business domains. • Design and maintain enterprise dimensional data models including fact tables, conformed dimensions, star schemas, snowflake schemas, and analytical data marts. • Translate business and reporting requirements into scalable analytical data structures and semantic data models. • Develop and maintain semantic layers, curated datasets, and business views to support enterprise reporting and analytics. • Design, develop, and maintain Power BI semantic models, datasets, dashboards, and reports for internal and external stakeholders. • Create and optimize DAX measures, calculated columns, KPIs, and business metrics to support operational and strategic reporting. • Implement Power BI best practices including Row-Level Security (RLS), deployment pipelines, performance optimization, and governance standards. • Partner with business users and subject matter experts to gather reporting requirements and deliver actionable analytics solutions. • Ensure consistency of business definitions, metrics, and calculations across enterprise reporting and analytics platforms. Data Governance and Compliance (10%) • Develop and enforce data governance standards, ensuring consistency, accuracy, and compliance with regulatory frameworks (e.g, HIPAA). • Implement data lineage, metadata management, and auditability practices using tools like AWS Glue Data Catalog. • Establish and manage data stewardship frameworks to improve data quality and trust across the organization. Performance Optimization and Security (10%) • Optimize system performance by designing and implementing data partitioning, indexing, and compression strategies. • Ensure data security through access controls, encryption, and secure design practices. Core Competencies • Experience with enterprise data modeling tools (e.g., Erwin, SQL Data Modeler) and strong expertise in dimensional modeling methodologies including Star Schema, Snowflake Schema, Fact and Dimension design, and semantic modeling. • Bachelor’s or master’s degree in computer science, Engineering, or related field. • 8+ years of experience in data engineering, with a strong emphasis on data governance and solution design. • Expertise in developing scalable data architectures for enterprise reporting • Familiarity with MLOps and AI data pipelines leveraging cloud-native services such as AWS SageMaker, Glue ML, or Databricks for feature engineering and model deployment. • Advanced knowledge of data governance tools and frameworks, including AWS Glue Data Catalog, to support enterprise-wide lineage, metadata, and compliance practices. • Strong understanding of cloud data platforms and services – particularly AWS (Redshift, S3, EMR, Lambda) and hybrid integrations with Azure Synapse or equivalent modern data warehouse technologies. • Proficiency in programming and scripting languages (Python, SQL, PySpark) for building testing and optimizing scalable data solutions. • Advanced experience developing Power BI semantic models, datasets, dashboards, reports, DAX measures, Power Query transformations, Row-Level Security, and performance optimization. Experience with Tableau is a plus. Additional Qualifications: • Excellent analytical and troubleshooting skills with attention to detail. • Strong communication skills to effectively articulate technical concepts to non-technical stakeholders. • Ability to prioritize tasks in a dynamic environment and manage multiple initiatives simultaneously. • Certifications in cloud, database, and programming are a plus.