AI Data Engineer II
UKG Bengaluru, Karnataka, India
Software Development · 10,001+ employees
About the role
Develop and maintain scalable ETL/ELT data pipelines using Python, PySpark, and SQL to support analytics and AI initiatives. Collaborate with cross-functional teams to process enterprise datasets and integrate them into modern cloud-based data platforms.
What they look for
Requirements
Requires 2-5 years of experience in data engineering with strong proficiency in Python, SQL, and Spark. Candidates must hold a bachelor's degree and demonstrate a willingness to learn emerging AI technologies like LLMs and vector databases.
Benefits
Full description
Why UKG:
At UKG, the work you do matters. The code you ship, the decisions you make, and the care you show a customer all add up to real impact. Today, tens of millions of workers start and end their days with our workforce operating platform. Helping people get paid, grow in their careers, and shape the future of their industries. That’s what we do.
We never stop learning. We never stop challenging the norm. We push for better, and we celebrate the wins along the way. Here, you’ll get flexibility that’s real, benefits you can count on, and a team that succeeds together. Because at UKG, your work matters—and so do you.
Role Overview We are looking for an AI Data Engineer with 2–5 years of experience in building and supporting scalable data pipelines and cloud-based data solutions. The role will primarily focus on data engineering using GCP, Python, PySpark, SQL, and cloud data platforms, while providing opportunities to work with emerging AI and Generative AI use cases. The ideal candidate should have strong data engineering fundamentals, hands-on experience with ETL/ELT pipelines, and an interest in applying data engineering skills to AI-enabled solutions. Key Responsibilities
- Develop and maintain ETL/ELT data pipelines for batch data processing and analytics workloads.
- Build data transformation solutions using Python, PySpark, and SQL.
- Work with Databricks to ingest, transform, process, and curate enterprise datasets.
- Integrate data from relational databases, APIs, files, and cloud storage.
- Support migration of datasets and pipelines from legacy or existing platforms to modern cloud-based data platforms.
- Perform data validation, reconciliation, and quality checks to ensure accuracy and completeness of migrated and processed data.
- Develop and maintain datasets and data models used by reporting, analytics, and downstream applications.
- Work with Azure Data Lake and related Azure data services for storing and processing enterprise data.
- Troubleshoot data pipeline failures, performance issues, and data quality problems.
- Participate in code reviews and follow standard development, testing, deployment, and CI/CD practices.
- Collaborate with Data Engineers, Analysts, Data Scientists, and business teams to understand data requirements.
- Support AI-related data requirements such as preparing and processing structured and unstructured datasets.
- Gain hands-on exposure to Generative AI concepts, LLMs and Retrieval-Augmented Generation (RAG) as part of AI-enabled data initiatives.
Required Skills
- 2–5 years of experience in Data Engineering, Data Analytics Engineering, or a related role.
- Good hands-on experience with Python.
- Strong working knowledge of SQL.
- Experience with Spark / PySpark for data processing.
- Hands-on experience with Databricks or a similar cloud data processing platform.
- Experience developing and maintaining ETL/ELT pipelines.
- Understanding of Data Lake / Lakehouse concepts.
- Experience working with structured and semi-structured data such as CSV, JSON, and Parquet.
- Understanding of data quality, data validation, and reconciliation techniques.
- Experience with at least one cloud platform, preferably Microsoft Azure.
- Familiarity with Git and CI/CD / DevOps practices.
- Good analytical and troubleshooting skills.
Candidates should be willing to learn and work with:
- Generative AI and Large Language Models (LLMs)
- Preparing enterprise data for AI use cases
- Embeddings and semantic search
- Vector databases / vector search
- Retrieval-Augmented Generation (RAG)
- AI-assisted data engineering and automation
Qualifications
- Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field.
- 2–5 years of relevant Data Engineering experience.
- Strong willingness to learn new data and AI technologies.
- Good communication, problem-solving, and collaboration skills.
Company Overview:
UKG is the Workforce Operating Platform that puts workforce understanding to work. With the world's largest collection of workforce insights, and people-first AI, our ability to reveal unseen ways to build trust, amplify productivity, and empower talent, is unmatched. It's this expertise that equips our customers with the intelligence to solve any challenge in any industry — because great organizations know their workforce is their competitive edge. Learn more at ukg.com.
UKG is proud to be an equal opportunity employer and is committed to promoting diversity and inclusion in the workplace, including the recruitment process.
Disability Accommodation in the Application and Interview Process
For individuals with disabilities that need additional assistance at any point in the application and interview process, please email UKGCareers@ukg.com
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