Senior Data Engineer

June 22

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Pierce Professional Resources

Temporary Staffing β€’ Contract Staffing β€’ Permanent Staffing β€’ Finance & Accounting Staffing β€’ IT Staffing & Recruiting

11 - 50

Description

β€’ Strategy Creation: Collaborate with cross-functional teams to define the data engineering strategy aligned to business objectives, including data modeling that unifies data assets across a range of source systems used to manage the operations of our partnering hospitals. β€’ Pipeline Development: Define and execute processes needed to develop, test, deploy, and maintain high quality data pipelines. Oversee the end-to-end development of data pipelines from source data extraction through to production-grade analytical dataset delivery, ensuring data quality and security throughout the pipeline. β€’ Performance Optimization: Continuously monitor and optimize data processing performance and efficiency. Identify and address bottlenecks, optimize query performance, and improve overall system stability. β€’ Data Governance: Establish and enforce data quality management policies, data access controls, and data privacy standards. β€’ Technical Leadership: Stay abreast of the latest developments in engineering tools and best practices. Provide guidance to the team about technical challenges. β€’ Documentation: Maintain clear and comprehensive documentation of data pipelines, architecture, and processes to ensure knowledge sharing and team continuity. β€’ Third-party Management: Evaluate and manage relationships with third-party vendors and tools, making informed decisions about when to leverage external solutions.

Requirements

β€’ Experience with the Azure cloud ecosystem β€’ Experience developing production-ready, real-time machine learning model serving pipelines β€’ Comfort developing in the Apache Spark Structured Streaming paradigm β€’ Experience working in a private equity-backed services company β€’ Experience deploying machine learning models with MLFlow or equivalent β€’ Experience developing CI/CD pipelines

Benefits

β€’ 3+ years in data engineering roles in a production environment β€’ Advanced proficiency in Python and SQL for data engineering β€’ Up-to-date knowledge of and 1+ years of experience using Databricks for Lakehouse management β€’ Deep understanding of data modeling, data architecture, and data integration best practices β€’ Strong hands-on experience with Apache Spark β€’ Familiarity with data governance, security, and privacy principles β€’ Comfort using git or equivalent to manage the software development life cycle β€’ Exceptional ability to learn and use new software development techniques and tools β€’ Ability to manage multiple projects simultaneously β€’ High energy, humble team player with "get it done" attitude, seeking collaboration with colleagues

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