1 month ago
Bengaluru, IndiaSenior
Responsibilities
- Lead the architecture and delivery of scalable batch and streaming data pipelines, data products, and lakehouse solutions.
- Translate business, reporting, analytics, and AI requirements into technical designs, data models, interfaces, and delivery plans.
- Build and review production-grade data solutions using Python, PySpark, SQL, Spark, BigQuery, Databricks, and Azure Data Lake.
- Establish reusable patterns for orchestration, transformations, metadata, schema evolution, incremental processing, and backfills.
- Guide raw, refined, and curated data modeling for understandable, reusable, performant datasets.
- Define standards for coding, peer review, testing, version control, CI/CD, release management, and operational readiness.
- Own pipeline reliability and performance, including monitoring, alerting, recovery, capacity planning, and cost optimization.
- Implement data quality, reconciliation, lineage, and observability controls.
- Partner with security, governance, architecture, platform, analytics, and business teams on access, privacy, retention, and compliance.
- Lead migration and modernization from legacy data platforms to cloud environments.
- Mentor data engineers, provide technical direction, unblock delivery, and support team development.
- Plan milestones, estimate effort, surface risks and dependencies, and communicate progress to stakeholders.
- Resolve complex production issues, perform root-cause analysis, and implement corrective actions.
- Prepare governed datasets for AI and Generative AI use cases, including retrieval, feature, and semantic search workflows.
- Evaluate tools and architectural options and document trade-offs related to scale, security, cost, and maintainability.
Requirements
- 6+ years of experience in data engineering, data platform engineering, or a closely related discipline, including ownership of production data systems.
- Experience leading technical delivery, mentoring engineers, and coordinating work across multiple teams or domains.
- Strong Python programming and advanced SQL skills, with hands-on PySpark or Spark experience.
- Deep understanding of cloud data architecture and lakehouse concepts, including storage, compute, partitioning, file formats, and workload design.
- Hands-on experience with major cloud data platforms; GCP and Azure experience, including BigQuery, Databricks, and Azure Data Lake, is preferred.
- Experience designing and operating ETL/ELT pipelines, workflow orchestration, data transformations, and reusable ingestion frameworks.
- Strong data modeling skills, including dimensional modeling and curated datasets for analytics and downstream applications.
- Experience with data quality, reconciliation, observability, lineage, metadata, and production monitoring.
- Working knowledge of role-based access, encryption, sensitive data handling, auditability, and other security and governance practices.
- Experience with Git-based development, automated testing, CI/CD, infrastructure or configuration management, and controlled deployments.
- Ability to troubleshoot distributed data-system performance and reliability issues and communicate findings clearly.
- Strong communication, planning, prioritization, and stakeholder management skills.
- Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field; an advanced degree is a plus.
- Experience owning solutions through design, implementation, deployment, and ongoing operations.
- Willingness to learn and work with Generative AI, LLMs, embeddings, vector search, semantic search, RAG, AI-assisted engineering, and evolving cloud data services.
Benefits
- Real workplace flexibility and benefits described as dependable by UKG.
- Equal opportunity employer committed to diversity and inclusion.
- Disability accommodations are available throughout the application and interview process.
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.