AI/ML Ops Engineer | Work From Home | Night Shift | Weekends Off

Power Smarter Workforce Technology With Reliable AI Systems

Reliable AI starts long before a model reaches production. Join as an AI/ML Ops Engineer and engineer the pipelines, infrastructure, governance, and data foundations that keep workforce technology performing at scale. Solve complex data management and analytics challenges internationally and take your technical career to the next level with Emapta.

Your Career Snapshot

• Employment Type: Full-time
• Shift: Night Shift, Weekends Off
• Work Setup: Work From Home

Exciting Perks Await!

• Day 1 HMO coverage with free dependent
• Competitive Salary Package
• Night differential pay to maximize your earnings
• Permanent WFH arrangement
• Fixed weekends off
• Salary Advance Program through our banking partner (Eligibility and approval subject to bank assessment. Available to account holders with minimum of 6 months company tenure.)
• Unlimited upskilling through Emapta Academy courses (Want to know more? Visit: https://emapta.com/training-calendar/)
• Free 24/7 access to our office gyms (Ortigas and Makati) with a free physical fitness trainer!
• Exclusive Emapta Lifestyle perks (hotel and restaurant discounts, and more!)
• Unlimited opportunities for employee referral incentives across the organization
• Standard government and Emapta benefits
• Total of 20 annual leaves to be used at your own discretion (including 5 credits convertible to cash)
• Fun engagement activities for employees
• Mentorship and exposure to global leaders and teams
• Career growth opportunities
• Diverse and supportive work environment

The Qualifications We Seek

Education

• High school diploma or equivalent
• Bachelor's degree in Computer Science, Information Systems, Engineering, Mathematics, Statistics, or a related field, preferred
• Equivalent combination of education, training, and relevant experience, considered

Skills & Experience

• 3 to 5 years of professional data engineering, AI/ML operations, or related experience, including ownership of a production data platform or major subject area
• Advanced SQL skills, including complex joins, window functions, incremental and merge patterns, query optimization, and execution plan interpretation
• Deep production experience with Snowflake, including warehouse and role design, Snowpark or stored procedures, streams and tasks, dynamic tables, secure data sharing, and consumption management
• Equivalent expertise in another cloud data warehouse, with demonstrated ability to quickly develop proficiency in Snowflake, considered
• Strong Python skills for data engineering, including modular, tested, and reviewable code
• Experience with complex transactional data modeling, including slowly changing dimensions, effective dating, and retroactive corrections
• Production experience with dbt, including model layering, testing, documentation, and continuous integration
• Hands-on experience with a major cloud platform, preferably AWS, including object storage, serverless and containerized compute, identity and access management, and secrets handling
• Experience with workflow orchestration tools, such as Airflow, Dagster, or Prefect, including backfill and recovery design
• Experience with vendor and partner data integrations, including flat files, SFTP, APIs, webhook-driven delivery, and source-of-truth reconciliation
• Experience with technical direction, engineering reviews, and team standards improvement
• Excellent written and verbal communication skills, with the ability to explain technical designs and trade-offs to non-technical audiences
• Ability to manage multiple priorities, deadlines, requests, and stakeholder expectations in a fast-paced environment
• Strong judgment in handling sensitive and regulated data, including privacy, security, and compliance concerns
• Experience in PEO, HR technology, payroll, benefits, insurance, or another regulated data environment, strongly preferred
• Familiarity with co-employment, multi-state jurisdictional logic, and audit trail requirements, preferred

Certifications / Licenses

• No certifications or licenses required
• SnowPro Advanced Data Engineer, AWS Certified Data Engineer, AWS Solutions Architect, or equivalent cloud or data platform certification, preferred

Competencies

• Communication: Communicate clearly, foster open dialogue and consensus, respect perspectives, exercise discretion, and propose effective solutions.
• Trust and Respect: Respect diverse perspectives and emotions, provide compassionate support, and foster trust through honesty and professionalism.
• Problem Solving: Identify issues, evaluate solutions, anticipate challenges, and apply effective resolution strategies.
• Accountability: Own decisions and actions, fulfill commitments, maintain confidentiality, and acknowledge mistakes.
• Client Focus: Assess stakeholder needs and service expectations, strengthen relationships, and meet or exceed internal and external requirements.

Your Daily Tasks

Essential Duties

• Architect the Snowflake platform across databases, schemas, warehouses, and roles, balancing performance, cost, security, and maintainability.
• Define source ingestion using batch loads, Snowpipe, Snowpipe Streaming, CDC, APIs, or third-party connectors based on latency, volume, reliability, and vendor constraints.
• Develop ingestion and integration pipelines for payroll, benefits, time and attendance, HRIS, ATS, general ledger, carrier, and vendor feeds, including reconciliation and failure handling.
• Design data models for retroactive payroll corrections, mid-period benefit changes, employee transfers, client onboarding/termination, effective dating, and historical restatements.
• Establish and enforce dbt standards for model layering, naming, testing, documentation, CI, and engineering reviews.
• Define pipeline controls for freshness, referential integrity, source-of-truth reconciliation, and anomaly thresholds, including alerting and triage.
• Implement orchestration using Airflow, Dagster, or equivalent, defining dependencies, retries, backfills, and pipeline service-level objectives.
• Optimize Snowflake clustering, queries, warehouse sizing, scaling, materialization, caching, and resource monitoring; report performance, consumption, and forecasts.
• Implement Snowflake governance and security through RBAC, row/column security, dynamic masking, object tagging, secure sharing, and access auditing.
• Translate PII, privacy, security, retention, regulatory, and contractual requirements into data models and access controls.
• Evaluate ingestion, orchestration, observability, and cataloging tools based on capability, cost, security, and operational requirements.
• Partner with ML/AI engineers on feature pipelines and the shared feature store for model training and inference.
• Partner with analytics/BI teams on semantic models, certified metrics, and delivery patterns replacing manual extracts and spreadsheets.
• Partner with software teams on application data design, integration contracts, and event schemas, assessing downstream impacts of upstream changes.
• Manage platform migrations and consolidations, including sequencing, cutover, parallel-run validation, and rollback criteria.
• Maintain architecture documentation, data dictionaries, lineage, and runbooks; provide evidence for internal audits, SOC examinations, and client due diligence.
• Provide technical direction and mentorship to data/analytics engineers and review code against engineering standards.
• Manage production data incidents, determining priorities and root causes and directing corrective and preventive actions.
• Estimate and plan work, define sequencing and dependencies, and communicate scope, timelines, risks, and trade-offs across teams.
• Apply AI tools to accelerate code generation, testing, and documentation while maintaining accuracy, privacy, and responsible use.
• Advise leadership on platform capabilities, limitations, technical debt, consumption forecasts, risks, investment priorities, and course corrections.

Other Duties

• Perform assigned duties and participate in business-hours data platform support rotations.
• Maintain technical expertise through training, industry publications, workshops, and current data engineering/platform practices.
• Improve pipeline reliability, engineering standards, documentation, and shared internal tools.
• Participate in special projects, cross-functional initiatives, and process improvements.
• Support team and business objectives through collaboration and knowledge sharing.

About the Client

Our client is a leading U.S.-based professional employer organization (PEO) that helps small and mid-sized businesses simplify workforce management and focus on growth. They deliver comprehensive solutions across payroll administration, HR management, employee benefits, recruiting, workplace safety, compliance, and HR technology. By combining experienced professionals with integrated workforce technology and data-driven solutions, they help employers reduce administrative complexity, manage compliance risks, improve employee experiences, and operate more efficiently as their businesses scale.

Join the Top 1% Talent. A better career. A better life.

Welcome to Emapta Philippines: home to professionals who choose growth, balance, and impact. Recognized as one of HR Asia's Best Companies to Work For in Asia 2025 and winner of Inspiring Workplaces Australasia 2026, Emapta offers more than opportunities -- it provides a career environment where people thrive. Collaborate with global teams, build meaningful expertise, and grow in a culture that prioritizes both performance and well-being.

Apply now and experience the difference!