Principal Data Engineer IRC279262

Overview

Work with product, product engineering, data engineering, and data science peers to build and support our AdTech platform.

Build data-oriented solutions that are simple, scalable, reliable, secure, maintainable, and make a measurable impact.

Provide our teams with the data they need to build, sell, and manage our platform, and scale DS prototypes into production solutions. Develop, deliver and maintain batch and real-time data pipelines, analysis services, workflows and orchestrations, and create and manage the platforms and data infrastructure that hold, secure, cleanse and validate, govern, and manage our data.

Manage our data platform, incorporating services using Airflow, CloudSQL, BigQuery, Kafka, Dataproc, and Redis running on Kubernetes and GCP.

Support our Data Science teams with access to data, performing code reviews, aiding model evaluation and testing, deploying models, and supporting their execution.

Employ modern pragmatic engineering principles, practices, and tooling, including TDD/BDD/ATDD, XP, QA Engineering, Trunk Based Development, Continuous Delivery, automation, DevSecOps, and Site Reliability Engineering.

Contribute to driving ongoing improvements to our engineering principles, practices, and tooling. Provide support & mentorship to junior engineers.

Develop and maintain a contemporary understanding of AdTech developments, industry standards, partner and competitor platform developments, and commercial models, from an engineering perspective.

Requirements

Must have 10+ years of experience

Experience architecting ML-based solutions in conjunction with DS teams, software engineering teams, and Product teams.

Proven experience translating data science prototypes into production services with clear APIs, SLAs/SLOs, and acceptance criteria in high-volume, low-latency contexts (e.g., AdTech).

Proven experience designing, building, and operating batch/streaming feature pipelines with schema control, validation, lineage, and offline/online parity using Python, Airflow/Composer, Kafka, and BigQuery; leveraging Spark, MySQL, and Redis as appropriate.

Proven experience implementing reproducible ML training workflows (data prep, hyperparameter tuning, evaluation) with artifact and model versioning on public cloud (GCP strongly preferred).

Proven experience packaging and deploying models as containers/services with staged promotion, canary/shadow/A/B rollouts, rollbacks, and environment parity via CI/CD.

Proven experience running scalable inference (batch, microservice, streaming) that meets latency/error budgets, with autoscaling, observability, and SRE-style reliability practices.

Proven experience establishing CI/CD for data and models with automated tests, data quality gates, model regression/drift detection, and API/data contract testing.

Proven experience applying DevSecOps in ML systems: IAM, secrets management, network policies, vulnerability scanning, artifact signing, and policy-as-code on GCP.

Proven experience collaborating with data science on feature design, labeling/annotation strategies, evaluation metrics, error analysis, and defining retraining triggers/schedules.

Exposure to contributing to product strategy and KPI definition; planning experiments (A/B) and prioritizing ML features aligned to SaaS delivery and operational needs.

Exposure to coaching and uplifting teams on data/ML testing, observability, CI/CD, trunk-based development/XP, and writing clear documentation (design docs, runbooks, model/data cards).

Proven experience operating in ambiguous, fast-changing environments; iterating from prototype to production with safe rollouts, clear ownership, and continuous improvement.

Strong English, excellent influencing and communication skills, and excellent documentation skills.

Job responsibilities

Work with product, product engineering, data engineering, and data science peers to build and support our AdTech platform.

Build data-oriented solutions that are simple, scalable, reliable, secure, maintainable, and make a measurable impact.

Provide our teams with the data they need to build, sell, and manage our platform, and scale DS prototypes into production solutions. Develop, deliver and maintain batch and real-time data pipelines, analysis services, workflows and orchestrations, and create and manage the platforms and data infrastructure that hold, secure, cleanse and validate, govern, and manage our data.

Manage our data platform, incorporating services using Airflow, CloudSQL, BigQuery, Kafka, Dataproc, and Redis running on Kubernetes and GCP.

Support our Data Science teams with access to data, performing code reviews, aiding model evaluation and testing, deploying models, and supporting their execution.

Employ modern pragmatic engineering principles, practices, and tooling, including TDD/BDD/ATDD, XP, QA Engineering, Trunk Based Development, Continuous Delivery, automation, DevSecOps, and Site Reliability Engineering.

Contribute to driving ongoing improvements to our engineering principles, practices, and tooling. Provide support & mentorship to junior engineers.

Develop and maintain a contemporary understanding of AdTech developments, industry standards, partner and competitor platform developments, and commercial models, from an engineering perspective.

What we offer

Culture of caring. At GlobalLogic, we prioritize a culture of caring. Across every region and department, at every level, we consistently put people first. From day one, you’ll experience an inclusive culture of acceptance and belonging, where you’ll have the chance to build meaningful connections with collaborative teammates, supportive managers, and compassionate leaders.

Learning and development. We are committed to your continuous learning and development. You’ll learn and grow daily in an environment with many opportunities to try new things, sharpen your skills, and advance your career at GlobalLogic. With our Career Navigator tool as just one example, GlobalLogic offers a rich array of programs, training curricula, and hands-on opportunities to grow personally and professionally.

Interesting & meaningful work. GlobalLogic is known for engineering impact for and with clients around the world. As part of our team, you’ll have the chance to work on projects that matter. Each is a unique opportunity to engage your curiosity and creative problem-solving skills as you help clients reimagine what’s possible and bring new solutions to market. In the process, you’ll have the privilege of working on some of the most cutting-edge and impactful solutions shaping the world today.

Balance and flexibility. We believe in the importance of balance and flexibility. With many functional career areas, roles, and work arrangements, you can explore ways of achieving the perfect balance between your work and life. Your life extends beyond the office, and we always do our best to help you integrate and balance the best of work and life, having fun along the way!

High-trust organization. We are a high-trust organization where integrity is key. By joining GlobalLogic, you’re placing your trust in a safe, reliable, and ethical global company. Integrity and trust are a cornerstone of our value proposition to our employees and clients. You will find truthfulness, candor, and integrity in everything we do.

About GlobalLogic

GlobalLogic, a Hitachi Group Company, is a trusted digital engineering partner to the world’s largest and most forward-thinking companies. Since 2000, we’ve been at the forefront of the digital revolution – helping create some of the most innovative and widely used digital products and experiences. Today we continue to collaborate with clients in transforming businesses and redefining industries through intelligent products, platforms, and services.