• Data Pipeline Design & Development: 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.
• Collaboration with Stakeholders: 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.
• ETL Implementation & Optimization: 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.
• Data Storage & Retrieval Optimization: Optimize the performance and cost-efficiency of data storage solutions and data retrieval methods within the cloud ecosystem.
• Data Quality & Security Assurance: Ensure data integrity, consistency, and security across all data pipelines, storage layers, and access points.
• Monitoring & Troubleshooting: Monitor data pipelines and associated infrastructure, troubleshooting and resolving any performance, data flow, or reliability issues.

• Innovation & Best Practices: Stay current with emerging trends and best practices in cloud computing, big data technologies, and data engineering methodologies to drive continuous improvement.

• Data Pipeline Design & Development: 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.
• Collaboration with Stakeholders: 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.
• ETL Implementation & Optimization: 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.
• Data Storage & Retrieval Optimization: Optimize the performance and cost-efficiency of data storage solutions and data retrieval methods within the cloud ecosystem.
• Data Quality & Security Assurance: Ensure data integrity, consistency, and security across all data pipelines, storage layers, and access points.
• Monitoring & Troubleshooting: Monitor data pipelines and associated infrastructure, troubleshooting and resolving any performance, data flow, or reliability issues.
• Innovation & Best Practices: Stay current with emerging trends and best practices in cloud computing, big data technologies, and data engineering methodologies to drive continuous improvement.

Do you have experience in Task prioritization?, Do you have a Bachelor’s degree?, The ideal candidate will have a strong background in data engineering with a specialization in Microsoft Azure and Databricks Lakehouse platforms. In this senior-level role, you will be responsible for designing, implementing, and maintaining robust and scalable data pipelines and architectures to support our data analytics and machine learning initiatives focusing on people data. If you’re passionate about transforming data into actionable insights and have expertise in cutting-edge data technologies, we encourage you to apply., We are seeking a highly skilled and experienced Principal HR Data Engineer to join our growing team. The ideal candidate will have a strong background in data engineering with a specialization in Microsoft Azure and Databricks Lakehouse platforms.

• 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.

DiscoverYourPath

• 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.

Acosta Group is a collective uniting the most trusted retail, marketing, and foodservice agencies-Acosta, ActionLink, CORE Foodservice, CROSSMARK, Mosaic, Premium Retail Services, and Product Connections. Together, we connect consumers with the brands they love through omnichannel selling, merchandising, brand advocacy, and integrated marketing. We recognize our associates are the foundation of our success. That’s why we prioritize your growth, development, and well-being to help you reach your full potential. With programs designed to support a fulfilling work-life balance, we offer opportunities that fit your lifestyle and ambitions-whether you’re looking for part-time flexibility or full-time career advancement. Ready for a career path that’s as unique as you? Discover your path at Acosta Group! Acosta Group is an equal opportunity employer and will ensure that applicants with disabilities are provided with reasonable accommodations. If reasonable accommodation is needed, please contact AskHR@acosta.com . Be sure to include “Applicant Accommodation” in the subject of your email to expedite the request. Acosta Group believes in good faith that the minimum and maximum annual salary or hourly compensation range for this opportunity is accurate and reasonable at the time of posting.

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