HR Data Engineer

Data Engineer HR Analytics

Hybrid - (Brentwood, TN)

3 month Contract (potential for extension)

Must Haves:
• Experience: 3 - 5 years experience in related field. (Software Engineer, Data Engineer, Data Analyst, Compter Analyst, DevOps Engineer, etc.)

Education:
• Bachelor's degree in computer science, Engineering, or related field. Any suitable combination of education and experience will be considered.

Other knowledge, skills, or abilities:
• Proven experience as a Data Engineer or similar Data related role.
• Expertise in Python programming and SQL and analytics tools such as Alteryx and PowerBI.
• Experience connecting multiple disparate data sources to support analytics processes and tools.
• Direct experience with large-volume data sets.
• Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
• Experience with big data tools and cloud-based analytical tools (MS Azure, Snowflake, Kafka, or similar).
• Experience building and optimizing data pipelines, architectures, and data sets.
• Strong analytic skills related to working with unstructured datasets.
• Strong expertise in ETL pipelines and API connections.
• Solid understanding of SQL, NoSQL, and other database technologies.
• Excellent problem-solving and communication skills.

Pluses:
• Alteryx experience
• Local to Nashville, coming onsite 2-3 days a week

Day to Day:
• As an HR Data Engineer, you will be responsible for designing, developing, and maintaining data models that support HR analytics and reporting. You will work closely with HR and IT teams to ensure data integrity, optimize data workflows, and provide actionable insights into strategies to drive data quality.
• Ensuring the accuracy, reliability, and consistency of HR data through regular cleaning and validation processes.
• Developing and maintaining database architectures to support HR data storage and retrieval.
• Develop high-quality data pipeline solutions using Python, and SQL.
• Transforming raw HR data into usable formats for analysis and reporting.
• Developing and maintaining database architectures to support HR data storage and retrieval.
• Working closely with HR professionals, data scientists, and other stakeholders to understand data needs and provide actionable insights.
• Implementing security measures to protect sensitive HR data and ensuring compliance with data privacy regulations.
• Automating data processes to improve efficiency and reduce manual intervention.