Staff Data Engineer, Data Platform

Job Summary

In this position as a Staff 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.

Responsibilities

Acts as a subject matter expert and thought leader within the Data Platform Domain

Data Strategy: Serves as a thought leader in data processing design and implementation, defining advanced structure for moving, storing, and maintaining high-quality data.

Team Leadership : Leads projects by managing timelines, coordinating teams, and communicating project statuses. Influences organizational direction through effective leadership and strategic collaboration

Data Governance and Security: Serves as a subject matter expert on governance standards, continuously aligning data practices with evolving industry best practices and requirements

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

Results Orientation: Establishes visionary goals, advises on strategic plans, employs advanced monitoring, influences high-level stakeholders, and delivers transformative results

Data Platform: Expansion of our Data Warehouse(s) and Lakehouse solutions for a healthcare data focused enterprise

Data Governance: Configuring and maintaining unity catalog to enable enterprise data lineage, data quality, auditability and data stewardship

Data Security: Building out Data Security protocols and best practices including the management of identified and de-identified (PHI/PII) solutions

Access Management: Always ensure a policy of least privilege is followed for anything being implemented

External Data Products: Building data solutions for clients while upholding the best standards for reliability, quality, and performance

ETL: Building solutions within Delta Live Tables and automation of transformations

Medallion Architecture: Building out performant enterprise-level medallion architecture(s)

Streaming and Batch Processing: Building fit-for-purpose near real-time streaming and batch solutions

Large Data Management: Building out performant and efficient enterprise solutions for internal and external users for both structured and unstructured healthcare data

Platform Engineering: Building out Infrastructure as Code using Terraform and Asset Bundles

Costs: Working with the business to build cost effective and cost transparent Data solutions

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

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

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

Integration with external systems utilizing API driven processes to ingest data

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

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

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

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

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

Qualifications

15+ years of relevant experience in design, development, and testing of Data Platform solutions, such as Data Warehouses, Data Lakes, and Data Products

Expert level experience working in Databricks and AWS

Expert level experience working in both relational and non-relational databases such as SQL Server, PostgreSQL, DynamoDB, DocumentDB

Experience managing and standardizing clinical data from structured and unstructured sources

Experience building and managing solutions on AWS

Expert knowledge in healthcare standards including FHIR, C-CDA, and traditional HL7

Expert knowledge in clinical standards/ontologies including ICD10/SNOMED/NDC/LOINC/Rx Norm

Expert in building out data models, data warehouses, designing of data lakes for enterprise and product use cases

Familiarity with designing and building APIs, ETL and data ingestion processes and utilization of tools to support enterprise solutions

Experience in performance tuning, query optimization, security, monitoring, and release management

Experience working with and managing large, disparate, identified and de-identified data sets from multiple data sources

Experience with building and deploying IAC using terraform, asset bundles and GitHub

Experience collaborating with Data Science teams and building AI based solutions to drive efficiencies and business value.

Wish list

Bachelor's degree or master's degree in computer science, data engineering or related field

Health and Life Insurance business experience

Professional level solution architecture certification in AWS