Principal Data Engineer IRC276334

Description

Requirements

• 10+ years of experience.
• Architect ML-based solutions with data science, software engineering, and product teams.
• Translate data science prototypes into production services with APIs, SLAs/SLOs, and acceptance criteria.
• Design and operate batch and streaming feature pipelines using Python, Airflow or Composer, Kafka, BigQuery, Spark, MySQL, and Redis.
• Implement reproducible ML training workflows and model versioning on public cloud, with GCP strongly preferred.
• Deploy containerized models with staged promotion, canary, shadow, A/B rollouts, rollback, and CI/CD.
• Apply DevSecOps for ML systems, including IAM, secrets, network policies, vulnerability scanning, artifact signing, and policy-as-code.
• Strong English, influencing, communication, and documentation skills.

Job Responsibilities

• Build and support the AdTech platform with product, engineering, data engineering, and data science peers.
• Develop batch and real-time pipelines, analysis services, workflows, orchestrations, and data infrastructure.
• Manage Airflow, CloudSQL, BigQuery, Kafka, Dataproc, Redis, Kubernetes, and GCP services.
• Support data science teams through data access, code review, model evaluation, testing, deployment, and execution.
• Apply modern engineering practices including testing, continuous delivery, DevSecOps, and SRE.
• Improve engineering practices and mentor junior engineers.
• Maintain knowledge of AdTech developments, standards, platforms, and commercial models.

What We Offer

• Flexible work schedules, work-from-home opportunities, paid time off, and holidays.
• Learning and development programs, technical and soft-skill training, and professional certifications.
• Competitive salaries, medical insurance, life and accident insurance, NPS, leave, bonuses, and referral bonuses.