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Senior Data Engineer at Pierce Professional Resources

Remote: 
Full Remote
Contract: 
Experience: 
Mid-level (2-5 years)
Work from: 
United States

Offer summary

Qualifications:

6+ years of experience in data engineering roles with a focus on data modeling and data architecture, Strong hands-on experience with Apache Spark, cloud computing technologies, Python, and SQL.

Key responsabilities:

  • Define data engineering strategy aligned with business goals
  • Oversee end-to-end development of data pipelines, optimize performance and efficiency
  • Establish data quality management policies and data governance standards
  • Stay updated on engineering tools, provide technical leadership, and manage third-party relationships
Pierce Professional Resources logo
Pierce Professional Resources Human Resources, Staffing & Recruiting SME https://www.pierce.com/
11 - 50 Employees
See more Pierce Professional Resources offers

Job description

  • 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.
  • 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.
  • Performance Optimization: Continuously monitor and optimize data processing performance and efficiency. Identify and address bottlenecks, optimize query performance, and improve overall system stability.
  • Data Governance: Establish and enforce data quality management policies, data access controls, and data privacy standards.
  • Technical Leadership: Stay abreast of the latest developments in engineering tools and best practices. Provide guidance to the team about technical challenges.
  • Documentation: Maintain clear and comprehensive documentation of data pipelines, architecture, and processes to ensure knowledge sharing and team continuity.
  • Third-party Management: Evaluate and manage relationships with third-party vendors and tools, making informed decisions about when to leverage external solutions.

Requirements

  • 6+ years in data engineering roles with progressively increasing responsibilities.
  • Deep understanding of data modeling, data architecture, and data integration best practices.
  • Strong hands-on experience with Apache Spark and cloud computing technologies.
  • Advanced proficiency in Python and SQL.
  • Familiarity with data governance, security, and privacy principles.
  • Comfort using collaboration tools such as GitHub or equivalent to manage development life cycle.
  • Excellent data modeling and engineering skills, and a talent for translating business objectives into technical solutions.
  • High energy, humble team player with “get it done” attitude, seeking collaboration with colleagues.
  • Ability to manage multiple projects simultaneously.
  • Experience engineering in Databricks strongly preferred.
  • 3+ years of software engineering with python in a production environment.
  • Experience with the Azure cloud ecosystem.
  • Experience developing production-ready, real-time machine learning model serving pipelines.
  • Comfort developing in the Apache Spark Structured Streaming paradigm.
  • Experience working in the veterinary services industry, or a private equity-backed services company.
  • Working knowledge of Microsoft Excel and Office 365.

Required profile

Experience

Level of experience: Mid-level (2-5 years)
Industry :
Human Resources, Staffing & Recruiting
Spoken language(s):
Check out the description to know which languages are mandatory.

Other Skills

  • Microsoft Excel
  • Collaboration
  • Teamwork

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