Staff Data Engineer, Data Platform

Job Description

Job Summary

\n

In this position as a Staff Health Data Engineer of client’s Data Platform, you will be a trusted advisor across leadership and engineering team, responsible for technical decisions. You will ensure data systems work together across our hybrid environments with a focus on scale and performance. You will lead technical and architecture decisions in collaboration with architecture and data engineering teams while ensuring compliance with industry-leading data privacy standards.

\n

\n

Responsibilities

\n

\n
• Acts as a subject matter expert and thought leader within the Data Platform Domain
\n
• Data Strategy: Serves as a thought leader in data processing design and implementation, defining advanced structure for moving, storing, and maintaining high-quality data.
\n
• Team Leadership : Leads projects by managing timelines, coordinating teams, and communicating project statuses. Influences organizational direction through effective leadership and strategic collaboration
\n
• Data Governance and Security: Serves as a subject matter expert on governance standards, continuously aligning data practices with evolving industry best practices and requirements
\n
• Project Management and Scope of Work: Contributes to defining the overall vision and strategy for data engineering within the organization, ensuring alignment with organizational goals and long-term objectives
\n
• Results Orientation: Establishes visionary goals, advises on strategic plans, employs advanced monitoring, influences high-level stakeholders, and delivers transformative results
\n
• Data Platform: Expansion of our Data Warehouse(s) and Lakehouse solutions for a healthcare data focused enterprise
\n
• Data Governance: Configuring and maintaining unity catalog to enable enterprise data lineage, data quality, auditability and data stewardship
\n
• Data Security: Building out Data Security protocols and best practices including the management of identified and de-identified (PHI/PII) solutions
\n
• Access Management: Always ensure a policy of least privilege is followed for anything being implemented
\n
• External Data Products: Building data solutions for clients while upholding the best standards for reliability, quality, and performance
\n
• ETL: Building solutions within Delta Live Tables and automation of transformations
\n
• Medallion Architecture: Building out performant enterprise-level medallion architecture(s)
\n
• Streaming and Batch Processing: Building fit-for-purpose near real-time streaming and batch solutions
\n
• Large Data Management: Building out performant and efficient enterprise solutions for internal and external users for both structured and unstructured healthcare data
\n
• Platform Engineering: Building out Infrastructure as Code using Terraform and Asset Bundles
\n
• Costs: Working with the business to build cost effective and cost transparent Data solutions
\n

\n

\n

Pipeline/ETL Management: You will help architect, build, and maintain robust and scalable data pipelines, monitoring, and optimizing performance

\n

Experience working with Migration tools i.e. Fivetran, AWS technologies and custom solutions

\n

\n

API Development: Drive our design and implementation of internal APIs for integrating data between different systems and applications

\n

Integration with external systems utilizing API driven processes to ingest data

\n

Develop APIs built on top of datasets for internal systems to consume data from Databricks

\n

Experience integrating with external APIs including but not limited to Salesforce, Financial systems, HR systems and other external systems

\n

\n

Data Modeling: Lead design, implementation, and maintenance of standards based (FHIR, OMOP, etc.) and efficient data models for both structured and unstructured data

\n

Collaboration: Partner internally and externally with key stakeholders to ensure we are providing meaningful, functional, and valuable data

\n

Processes and Tools: Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.

\n

\n

Qualifications

\n

\n
• 15+ years of relevant experience in design, development, and testing of Data Platform solutions, such as Data Warehouses, Data Lakes, and Data Products
\n
• Expert level experience working in Databricks and AWS
\n
• Expert level experience working in both relational and non-relational databases such as SQL Server, PostgreSQL, DynamoDB, DocumentDB
\n
• Experience managing and standardizing clinical data from structured and unstructured sources
\n
• Experience building and managing solutions on AWS
\n
• Expert knowledge in healthcare standards including FHIR, C-CDA, and traditional HL7
\n
• Expert knowledge in clinical standards/ontologies including ICD10/SNOMED/NDC/LOINC/Rx Norm
\n
• Expert in building out data models, data warehouses, designing of data lakes for enterprise and product use cases
\n
• Familiarity with designing and building APIs, ETL and data ingestion processes and utilization of tools to support enterprise solutions
\n
• Experience in performance tuning, query optimization, security, monitoring, and release management
\n
• Experience working with and managing large, disparate, identified and de-identified data sets from multiple data sources
\n
• Experience with building and deploying IAC using terraform, asset bundles and GitHub
\n
• Experience collaborating with Data Science teams and building AI based solutions to drive efficiencies and business value.
\n

\n

\n

Wish list

\n

\n
• Bachelor's degree or master's degree in computer science, data engineering or related field
\n
• Health and Life Insurance business experience
\n
• Professional level solution architecture certification in AWS
\n

\n