Acosta

Principal HR Data Engineer

Acosta

full-time

Posted on:

Location Type: Hybrid

Location: LewisvilleTexasUnited States

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About the role

  • Design, develop, and maintain scalable, high-performance data pipelines and architectures leveraging Microsoft Azure and Databricks Lakehouse to enable data analytics and machine learning capabilities.
  • Partner with data scientists, data analysts, business teams, and other stakeholders to understand data requirements and ensure high-quality data solutions are delivered in alignment with business needs.
  • Implement and optimize ETL (Extract, Transform, Load) processes for the ingestion, transformation, and loading of data from diverse data sources into the Databricks Lakehouse environment.
  • Optimize the performance and cost-efficiency of data storage solutions and data retrieval methods within the cloud ecosystem.
  • Ensure data integrity, consistency, and security across all data pipelines, storage layers, and access points.
  • Monitor data pipelines and associated infrastructure, troubleshooting and resolving any performance, data flow, or reliability issues.
  • Stay current with emerging trends and best practices in cloud computing, big data technologies, and data engineering methodologies to drive continuous improvement.

Requirements

  • Bachelor's degree in Computer Science, Information Technology, Data Engineering, or a related field
  • Relevant certifications—such as Microsoft Certified: Azure Data Engineer or Databricks Certified Data Engineer—are a plus.
  • 7 or more years of experience as a Data Engineer with a focus on Microsoft Azure and Databricks Lakehouse technologies.
  • Demonstrated experience working with HR or People data is strongly preferred, particularly within enterprise HCM, workforce analytics, or employee lifecycle reporting environments.
  • Experience in designing, developing, and optimizing scalable data solutions in cloud environments.
  • Working knowledge of machine learning and AI data pipelines, including how data engineering supports feature engineering, model training, and scalable analytics.
  • Strong background in SQL, Python, PySpark, and other relevant programming languages.
  • Extensive experience in ETL processes, data integration, and data warehousing.
  • Data Management: Expertise in data modeling, data quality assurance, and applying industry-standard data governance practices.
  • Cloud & Big Data Technologies: Familiarity with tools and frameworks like Azure Synapse, Azure Databricks, Apache Kafka, and Azure Data Factory.
  • Problem Solving: Strong analytical and troubleshooting skills with an attention to detail.
  • Collaboration: Excellent communication and collaboration skills to work effectively with cross-functional teams.
  • Independence & Time Management: Ability to work autonomously, manage multiple projects, and prioritize tasks efficiently.
Benefits
  • We prioritize your growth, development, and well-being to help you reach your full potential.
  • Opportunities that fit your lifestyle and ambitions—whether you’re looking for part-time flexibility or full-time career advancement.
  • Reasonable accommodations for applicants with disabilities.
Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools
data engineeringETLdata modelingdata quality assuranceSQLPythonPySparkmachine learningdata integrationdata warehousing
Soft Skills
problem solvinganalytical skillsattention to detailcommunication skillscollaborationindependencetime management
Certifications
Microsoft Certified: Azure Data EngineerDatabricks Certified Data Engineer