Data Engineer

Dallas College • Dallas, TX

10d • $66,900 • Onsite

About The Position

This role will help maintain and improve data pipelines, Lakehouse tables, and quality checks that feed HR dashboards and reporting. The Data Engineer I will work with the People Analytics team, HRIS, and IT to ensure that HR data is accurate, reliable, and ready for analysis. This is a hands-on learning role ideal for someone early in their data engineering or analytics career who wants experience with cloud data platforms, HR workflows, and enterprise-scale reporting. The Data Engineer I will assist senior staff with pipeline development, data modeling, and data governance activities while gaining exposure to advanced tools such as Microsoft Fabric, Delta Lake, and Workday RaaS integrations.

Requirements

• Foundational understanding of data pipelines, ETL/ELT, and data modeling.
• Ability to write Python/R scripts and SQL queries.
• Willingness to learn Delta Lake, distributed computing, and cloud analytics architecture.
• Exposure to API concepts and structured data formats (JSON, CSV, XML).
• Ability to quickly learn HR business logic and translate it into structured data.
• Ability to document logic, follow modeling patterns, and understand existing data flows.
• Skill in building clean, reproducible datasets with clear lineage.
• Ability to think through upstream/downstream impacts when modifying logic.
• Ability to test and validate data pipelines and identify root causes of errors.
• Willingness to work with version control, CI/CD concepts, and notebook-based workflows.
• Ability to produce maintainable, well-documented code.
• Clear communication with partners who have varying levels of technical expertise.
• Ability to translate technical steps into meaningful explanations.
• Reliability in meeting deadlines and coordinating with HR, IT, and People Analytics teams.
• High attention to detail and a strong sense of responsibility for data quality.
• Desire to grow technical skills and take on progressively complex engineering work.
• Adaptability in a fast-evolving analytics environment with new tools and technologies.
• 0–2 years of experience in data engineering, data analytics, or related technical work (internship or project experience acceptable).
• Foundational knowledge of Python or R and SQL.
• Understanding of basic ETL/ELT concepts, data cleaning, and data transformation.
• Ability to learn REST APIs, JSON parsing, and automated ingestion patterns.
• Basic understanding of data modeling concepts such as tables, joins, relational structure, and time-series data.
• Familiarity with Git/GitHub or willingness to learn.
• Bachelor’s degree in Computer Science, Information Systems, Data Analytics, Statistics, or related field.
• Equivalent experience or technical certifications (e.g., Azure, Databricks, Python) also considered.
• Will be subject to a criminal background check.
• Some positions may be subject to a fingerprint check.

Nice To Haves

• Familiarity with cloud data tools (e.g., Microsoft Fabric, Databricks, Snowflake, Azure, or similar) preferred.
• Exposure to HRIS or enterprise systems (e.g., Workday, PeopleSoft, SAP).
• Experience with Power BI, semantic models, or dashboard development.
• Coursework or project experience with Delta Lake or distributed computing.
• Some knowledge of DAX, R, PySpark/SparkR, or statistical modeling.
• Exposure to data governance concepts (data quality, metadata, lineage).

Responsibilities

• Assist in maintaining automated data ingestion from HR source systems (e.g., Workday RaaS, Qualtrics, ServiceNow) using REST APIs and scheduled notebooks.
• Help build and troubleshoot ETL/ELT processes using Python, PySpark/SparkR, SQL, and Microsoft Fabric notebooks.
• Support the creation and maintenance of Delta Lake/Lakehouse tables, including basic schema updates and monthly snapshots.
• Monitor pipeline executions and assist with logging, error handling, and basic performance improvements.
• Contribute to data quality checks to ensure timely and accurate HR datasets.
• Help transform raw HR data into structured, analysis-ready datasets for headcount, turnover, recruitment, learning, compensation, and other domains.
• Support development of semantic layers, shared dimensions, and metric definitions used by Power BI dashboards.
• Follow established data governance practices, including naming conventions, documentation, and metadata capture.
• Assist analysts by preparing clean datasets, writing optimized queries, and supporting reproducible analytics workflows.
• Help maintain trended metrics, time-series tables, and other recurring data structures needed for enterprise reporting.
• Ensure that models are structured to support Power BI dashboard needs and self-service analytics.
• Work with People Analytics team, HRIS, and IT to support Dallas College’s People Analytics roadmap.
• Participate in data governance efforts, security reviews, and documentation updates.
• Contribute to knowledge transfer by writing clear notes, process guides, and pipeline documentation.
• Engage in professional development to learn best practices in data engineering, cloud analytics, and HR data structures.

Benefits

• Normal physical job functions performed within a standard office environment. Reasonable accommodation(s) may be made to individuals with physical challenges to perform the essential duties and responsibilities
• Required Dallas College Professional Development Hours per Academic Year. All employees are required to complete a minimum of 19 hours.

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level