Staff Software Engineer - ENG - {GCP Data Engineering}

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 experienced Staff Data Engineer with overall experience and strong hands-on expertise in building and maintaining enterprise-scale data engineering solutions on Google Cloud Platform (GCP).

The ideal candidate should have extensive experience designing, developing, deploying, and supporting batch and real-time data pipelines using the GCP data engineering ecosystem. The candidate should also have a good understanding of broader GCP cloud services, security, monitoring, CI/CD, and production support practices required to operate reliable data platforms.

Exposure to AI/ML, Vertex AI, Generative AI, or data engineering for ML workloads will be an additional advantage.

Key Responsibilities

• Design, develop, and maintain scalable batch and streaming data pipelines on Google Cloud Platform.
• Build enterprise data processing solutions using services such as BigQuery, Dataflow, Dataproc, Cloud Storage, Pub/Sub, and Cloud Composer.
• Develop robust ETL/ELT frameworks for ingesting data from databases, APIs, files, messaging platforms, and other enterprise data sources.
• Design and optimize data models and datasets in BigQuery for analytics and downstream consumption.
• Develop data transformation and processing components using Python, SQL, Apache Beam, and/or Spark.
• Build workflow orchestration and scheduling solutions using Cloud Composer / Apache Airflow.
• Implement real-time and event-driven data processing using Pub/Sub and Dataflow.
• Ensure pipelines meet requirements for performance, scalability, reliability, data quality, security, and cost optimization.
• Implement appropriate logging, monitoring, alerting, retry, reconciliation, and error-handling mechanisms for production pipelines.
• Troubleshoot production issues, perform root-cause analysis, and implement permanent fixes.
• Participate in production deployments, maintenance activities, and operational support of data platforms.
• Work with DevOps and Cloud Engineering teams to implement CI/CD and Infrastructure-as-Code practices for data engineering workloads.
• Implement GCP security best practices including IAM, service accounts, secrets management, encryption, and least-privilege access.
• Collaborate with data architects, analysts, application teams, ML engineers, and business stakeholders to translate requirements into scalable technical solutions.
• Participate in technical design reviews, code reviews, performance optimization, and engineering best practices.
• Mentor junior engineers and contribute to reusable data engineering frameworks, standards, and patterns.

Required Technical Skills

GCP Data Engineering

Strong hands-on experience with the GCP data engineering stack, including:

• Google BigQuery
• Google Cloud Storage (GCS)
• Google Cloud Dataflow
• Google Cloud Dataproc
• Google Cloud Pub/Sub
• Cloud Composer / Apache Airflow

Experience designing and implementing both batch and streaming data pipelines is expected.

Programming & Data Processing

• Strong hands-on programming experience with Python.
• Advanced knowledge of SQL, including complex queries and query optimization.
• Experience with Apache Beam and/or Apache Spark.
• Strong understanding of ETL/ELT design patterns.
• Experience working with structured, semi-structured, and large-scale datasets.
• Good understanding of data modeling, partitioning, clustering, schema evolution, and performance optimization.

GCP Cloud Platform

Good working knowledge of broader GCP services and concepts such as:

• IAM and Service Accounts
• Secret Manager
• Cloud Logging and Cloud Monitoring
• Compute Engine / Cloud Run / GKE exposure
• VPC and basic networking concepts
• Cloud Scheduler / Cloud Functions where applicable
• GCP security and access-control best practices
• Cost monitoring and optimization

DevOps / CI-CD

• Experience implementing CI/CD for data engineering applications.
• Familiarity with tools such as Git, Jenkins, GitHub Actions, GitLab CI, or Cloud Build.
• Exposure to Infrastructure-as-Code using Terraform is preferred.
• Experience with containerization using Docker is desirable.
• Understanding of automated testing and deployment practices for data pipelines.

Data Engineering & Architecture Knowledge

The candidate should have a strong understanding of:

• Data lakes and cloud data warehouses
• ETL vs. ELT architectures
• Batch vs. streaming architectures
• Data ingestion and integration patterns
• Data modeling and dimensional modeling
• Data quality and reconciliation
• Metadata and schema management
• Data security and governance
• Pipeline observability and monitoring
• Performance and cost optimization
• High availability and fault-tolerant pipeline design

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 [email protected]