1 month ago
Bengaluru, IndiaMid Level / Senior
Responsibilities
- Develop and maintain ETL/ELT pipelines for batch processing and analytics workloads.
- Build data transformation solutions using Python, PySpark, and SQL.
- Use 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 to modern cloud-based data platforms.
- Perform data validation, reconciliation, and quality checks.
- Develop and maintain datasets and data models for reporting, analytics, and downstream applications.
- Work with Azure Data Lake and related Azure data services.
- Troubleshoot pipeline failures, performance issues, and data quality problems.
- Participate in code reviews and follow development, testing, deployment, and CI/CD practices.
- Collaborate with Data Engineers, Analysts, Data Scientists, and business teams on data requirements.
- Prepare and process structured and unstructured datasets for AI-enabled solutions.
- Learn and contribute to Generative AI, LLM, embeddings, semantic search, vector search, and RAG initiatives.
Requirements
- 2–5 years of experience in Data Engineering, Data Analytics Engineering, or a related role.
- Bachelor’s degree in Computer Science, Information Technology, Engineering, or a related field.
- Hands-on experience with Python, SQL, Spark or PySpark, Databricks or a similar cloud data processing platform, and ETL/ELT pipelines.
- Understanding of Data Lake and Lakehouse concepts.
- Experience with structured and semi-structured data including CSV, JSON, and Parquet.
- Understanding of data quality, validation, and reconciliation techniques.
- Experience with at least one cloud platform, preferably Microsoft Azure.
- Familiarity with Git and CI/CD or DevOps practices.
- Strong analytical, troubleshooting, communication, problem-solving, and collaboration skills.
- Willingness to learn Generative AI, LLMs, enterprise AI data preparation, embeddings, semantic search, vector databases, vector search, RAG, and AI-assisted data engineering.
Benefits
- Flexible work arrangements are offered.
- UKG provides benefits described as dependable and supportive.
- The company promotes learning, collaboration, and employee development.
Tech Stack
Categories
Data Engineering
About UKG
UKG builds cloud software for human capital and workforce management—HR, payroll, timekeeping, and scheduling—sold as SaaS to mid‑size and large employers. Formed in 2020 by the merger of Ultimate Software and Kronos, it is privately held by Hellman & Friedman and has dual headquarters in Lowell, Massachusetts, and Weston, Florida. Its platform helps organizations handle pay, compliance, and workforce planning across industries.