Overview

The senior data engineer is responsible for the successful delivery of business intelligence information to the entire organization and is experienced in Data Warehouse and BI development implementations. He/she will be part of the team to review, analyze, modify, and create ETLs, testing, debugging, integration and implementation processes. Tasks will also include documenting technical needs for ETL processes and databases, and ensuring optimal technical infrastructure is utilized. This position involves the delivery of big data integration projects and requires leveraging best practices expertise and experience at implementation; as well as effective technology know-how to support the ongoing activity of those working within business intelligence and analytics teams.

ESSENTIAL FUNCTIONS

• Design, construct, install, test and maintain highly scalable data management systems
• Develop and maintain logical & physical data model designs, data management standards and conventions, data naming standards and metadata (normalized, de-normalized and STAR-based structures)
• Perform reverse engineering of physical data models from databases and SQL scripts
• Evaluate data models and physical databases for variances and discrepancies
• Knowledge of the Healthcare Ecosystem and Use Cases - e.g., Care Workflows, Careplans, Prior Auth, Population Health, Segmentation/Stratification, Risk Computation, etc.
• Understanding and knowledge of Terminology Standards such as ICD10, CPT, Snomed, LOINC, RXNorm, ERGs, RERGs, DRGs
• Experience in a healthcare setting with deep exposure to Payer and Provider oriented terminologies (Nice to Have).
• Validate business data objects for accuracy and completeness
• Participate in higher level planning efforts. Play a role in definition of process/guidelines/standards
• Direct support of business intelligence and analytics teams

LEADERSHIP

• Comfortable engaging with personnel at all levels of leadership
• Ability to listen to others and incorporate good ideas regardless of source
• Professional in all communication and interaction with others
• Willing to admit mistakes and make course corrections quickly

ANALYSIS & COMMUNICATION

• Ability to assess/analyze information needs objectively
• Ability to drill down and ask the right questions to arrive at root cause
• Confident in front of both management and developer audiences; ability to customize communication for both
• Ability to learn and adapt quickly to new business domains and technologies
• Good written communication skills; ability to use correct grammar and structure communication in a way that makes it easy to understand
• Ability to navigate difficult conversations, remain objective and achieve sound outcomes

TECHNOLOGY & CAPABILITIES REQUIRED

• SQL: wide variety of development from simple ad hoc queries to complex stored procedures and multidimensional analysis
• Data integration: ETL and ELT development paradigms and platforms – Airflow, Azure Data Factory, Apache Spark, Databricks
• Software development methodologies/concepts: SDLC, Agile, Scrum, Git, Continuous Integration
• MPP Data Warehouse Platforms: Azure Synapse (SQL DW), Amazon Redshift, Snowflake, Teradata, Azure Data Lake
• Programming/scripting languages: Scala, Python, and PowerShell
• Cloud Platforms: Azure Data Lake, Azure SQL DW, Azure Databricks, Apache Spark, AWS (Redshift)
• Data profiling/quality: Informatica, Microsoft
• Performance Tuning: Expert in performance tuning of ETL/SQL code
• Required experience in documentation of code or data models and data mapping, definition of process/guidelines/standards, create data dictionaries, etc.
• Experience with history tables, fact vs. dimension tables (slowly changing dimensions, SCD type 2), Git and Source Control, Azure cloud, Data Lake, Data Factory, Synapse
• Working knowledge of SOLID development principles and common data models such as HL7, OMOP, FHIR, OMOP on FHIR, etc.
• Expertise in SQL