Role Description As a Senior Principal Data Engineer within the Enterprise Data & Analytics Office, you will lead the design, evolution, and operational excellence of Nexus, UKG’s unified, GCP-based data platform, enabling analytics, AI, and enterprise decision-making at scale. You will translate architectural vision into reliable, scalable, cost-efficient data systems, lead platform modernization efforts, and set the engineering bar for data ingestion, transformation, and operational analytics across UKG. Key Responsibilities - Enterprise Data Engineering Leadership - Drive the implementation of standardized medallion architecture (Bronze–Silver–Gold) across all domains. - Establish and enforce engineering patterns for batch, streaming, CDC, and event-driven pipelines. - Drive design patterns for Fact and Dimension modeling, data mesh, and change data capture (CDC). - Platform & Pipeline Excellence - Design and evolve scalable data pipelines using GCP-native services (BigQuery, GCS, Composer, Pub/Sub, Dataflow) and Databricks (Delta Lake, DLT). - Ensure platform reliability, performance, and scalability for petabyte-scale analytics workloads. - Lead engineering decisions around partitioning, clustering, query optimization, and cost controls (FinOps). - Own observability standards (freshness, SLAs, error handling, monitoring). - Engineering Standards, Quality & Governance - Define and enforce engineering standards for data quality, testing, CI/CD, and production readiness. - Implement automated data quality frameworks, lineage, and metadata integration in partnership with Data Governance and Architecture teams. - Ensure all pipelines meet SOX, security, and auditability requirements. - Partner with Architects to ensure engineering implementations align to enterprise reference architectures. - Cross-Functional Delivery & Influence - Partner with Product Managers, Product Owners, Architects, and Analytics leaders to deliver high-impact data capabilities. - Act as the technical escalation point for complex production issues and platform risks. - Influence roadmap decisions by balancing technical feasibility, delivery velocity, and long-term sustainability. - Support ESE Agile delivery by enabling architecture runway and reducing technical blockers. - Mentorship & Organizational Impact - Mentor Principal, Senior, and Mid-level Data Engineers, raising the overall engineering maturity of the organization. - Lead by example through design reviews, code reviews, and engineering forums. - Build reusable frameworks, libraries, and accelerators that scale engineering productivity. - Foster a culture of ownership, quality, and continuous improvement. Qualifications - 15+ years of experience in data engineering, data platforms, or large-scale analytics systems. - Proven leadership delivering enterprise-scale data platforms and migrations. - Deep hands-on experience with large (Petabyte) scale operating data platforms. Technical Expertise - GCP (required): BigQuery, GCS, Cloud Composer, Pub/Sub, Dataflow, Dataform, Dataproc, Dataplex - Databricks: Delta Lake, Delta Live Tables, Spark, Unity Catalog - Strong proficiency in Python, SQL, Spark, and distributed systems - Expertise in data modeling, ELT patterns, CDC, and streaming architectures - Experience supporting AI/ML pipelines, feature stores, and analytics consumption - Strong understanding of Dimensional Modeling, ELT and modern data lakehouse patterns. Leadership & Collaboration - Proven ability to influence without authority across engineering, product, and architecture teams. - Strong communication skills with both technical and executive audiences. - Track record of mentoring senior engineers and leading complex initiatives. Preferred Qualifications - Experience modernizing legacy warehouses and ETL platforms. - Familiarity with Data Mesh execution and domain-aligned data products. - Experience implementing FinOps practices for analytics platforms. - Exposure to AI/ML enablement, feature engineering, or agent-driven analytics. - Google Cloud certifications (Data Engineer, Architect) preferred. Benefits - The pay range for this position is $184,300 to $230,000. - The actual base pay offered may vary depending on skills, experience, job-related knowledge, and work location. - In addition to base pay, employees may be eligible to participate in a performance-based bonus plan and to receive restricted stock unit awards as part of total compensation. - Learn more about UKG’s benefits and rewards at UKG Benefits .

Role Description We are seeking a Lead Data Scientist to help build and scale advanced Machine Learning solutions. This role is ideal for a strong Data Scientist with solid coding capabilities, hands-on ML experience, and exposure to MLOps practices. The selected candidate will play a key role in designing, developing, and deploying ML models while collaborating with cross-functional teams and contributing to technical leadership initiatives. - Design, develop, and deploy Machine Learning models to solve business problems. - Write production-level code to support scalable ML solutions. - Collaborate with data engineers and software engineers to integrate ML models into production environments. - Contribute to the implementation of MLOps best practices for model monitoring, versioning, and deployment. - Work with cloud platforms (AWS, GCP, or similar) to build and maintain ML infrastructure. - Partner with stakeholders to translate business needs into data-driven solutions. - Provide technical guidance and mentorship to junior team members. - Communicate technical findings and recommendations clearly to both technical and non-technical audiences. Qualifications - Strong knowledge of Machine Learning algorithms and modeling techniques. - Solid programming skills (Python or similar language). - Experience working with cloud platforms such as AWS or GCP. - Exposure to MLOps practices and model deployment processes. - Experience working with data pipelines and ML lifecycle management. - Strong analytical and problem-solving skills. - Excellent communication skills and ability to work collaboratively in cross-functional teams. - Positive, proactive, and curious mindset. Benefits - Learning Opportunities: - Certifications in AWS (we are AWS Partners), Databricks, and Snowflake. - Access to AI learning paths to stay up to date with the latest technologies. - Study plans, courses, and additional certifications tailored to your role. - Access to Udemy Business, offering thousands of courses to boost your technical and soft skills. - English lessons to support your professional communication. - Travel opportunities to attend industry conferences and meet clients. - Mentoring and Development: - Career development plans and mentorship programs to help shape your path. - Celebrations & Support: - Special day rewards to celebrate birthdays, work anniversaries, and other personal milestones. - Company-provided equipment. - Flexible working options to help you strike the right balance. - Other benefits may vary according to your location in LATAM. For detailed information regarding the benefits applicable to your specific location, please consult with one of our recruiters.

Role Description As a Data Mining Ideation Specialist, you will leverage your deep expertise in medical coding requirements, claims adjudication processes, and reimbursements methodologies to design and develop data mining audits that drive payment accuracy across our clients' Medicaid, Medicare, and Commercial lines of business. This role is ideal for someone who thrives at the intersection of coding, analytics, and audit development. - Translate complex reimbursement policies into actionable audit concepts that identify improper payments with a high degree of precision and consistency. - Apply strong analytical thinking, an in-depth understanding of claims data, and meticulous attention to detail to uncover overpayment opportunities and build scalable audit logic. - Define data selection parameters, validate outcomes, and continuously refine audit strategies to improve accuracy and impact. - Support production audit teams through training, guidance, and ongoing quality initiatives. This is a remote role. Salary Range 80-100K depending upon experience. Qualifications - 5+ years of complex claims processing and/or coding auditing experience in the health insurance industry. - Knowledge of all payer types including Medicare, Medicaid, and Commercial plans. - Prior experience in payment integrity audit development is highly preferred. - Mastery of CPT, HCPCS, and ICD coding standards. - Current Coding Certification: - AAPC Certified Professional Coder (CPC), Certified Outpatient Coder (COC) certification, or - Certified Coding Specialist (CCS) certification through AHIMA or - RHIT designation - Expert level understanding of medical claim coding and its impact on claim payments. - Ability to develop data mining audits, apply regulatory standards, and contractual requirements with credibility and objectivity. - Knowledge of legal, regulatory, and policy compliance issues related to medical coding and billing procedures and documentation. - Knowledge of health insurance operations, specifically with claims processing, billing, reimbursement, or provider contracting. - Prior experience in payer edit development, and/or reimbursement policy experience. - Expertise in data analysis and EXCEL. - Strong analytical and problem-solving abilities. - Effective communication skills. - Meticulous attention to detail. Requirements - Python or SQL coding skills. - Clinical background or experience. - Demonstrated experience translating technical jargon to non-technical end users. - Previous experience in the Payment Integrity space. - Exposure to EDI transactions (837, 835). - Experience using coding tools (such as 3M, Webstrat, and Encoder). - Collaborative mindset and ability to work effectively across cross-functional teams. - Proficiency in Outlook, Word, Excel, and other applications. - Ability to work independently and can multi-task or transition to different tasks easily. What Success Looks Like - Develop and deliver 6+ new audit concepts monthly, including logic specifications aligned with reimbursement policies. - Submit 4+ high-impact audit concepts per month, contributing to a minimum of $975K in identified overpayment opportunities. - Partner with internal teams to move concepts from ideation to client review and production implementation. - Ensure timely communication and follow-through: - Respond to inquiries within 1 business day. - Complete research and provide updates within 3 business days. - Drive resolution, including logic revisions or claim actions, within 5 business days. - Monitor audit performance, including yield and appeal outcomes, and continuously refine logic for accuracy and impact. - Collaborate with Operations and Management to support audit effectiveness and quality initiatives. - Complete "Second Look" reviews within established turnaround times.

• Develop, validate, and maintain MLOps pipelines, ensuring automation and integration with AWS services; • Design, implement, and evolve system architecture in a cloud environment; • Ensure the support, maintenance, and evolution of the workflow automation tool (n8n); • Collaborate with data scientists to operationalize and deploy Machine Learning models and LLMs; • Act on incident resolution and support tickets related to the MLOps environment; • Propose and develop technical solutions such as web applications, APIs, and agents based on LLMs; • Build and integrate APIs to support applications and data flows; • Monitor and optimize the performance of pipelines, applications, and production services.