Valtech

Valtech

Valtech is a global business transformation company specializing in technology, marketing, and experience design to help clients innovate, connect with consumers, and optimize ROI.

Professional Services
5K-10K
Founded 1993

Description

  • Build and support batch, distributed, and real-time highly available data pipelines.
  • Develop fault-tolerant, self-healing, adaptive, and highly accurate data processing pipelines.
  • Lead implementation of complex data programs and provide technical consultation.
  • Develop and maintain documentation for assigned systems and projects.
  • Tune distributed queries across billions of rows of data.
  • Perform root cause analysis and resolve software or business process issues.
  • Implement and maintain dbt transformation models, CI pipelines, and data contracts for campaign-related marts.
  • Build and monitor data quality gates, reconciliation checks, and freshness SLOs.
  • Optimize BigQuery cost and performance through query tuning, storage design, and reservation strategy.
  • Implement platform hardening controls such as retries, dead-letter queues, DR runbooks, and VPC-SC/DLP validation support.

Requirements

  • Strong expertise in Python for data pipelines, processing tasks, and automation.
  • Advanced SQL proficiency, including nested fields and analytic functions.
  • Hands-on experience with core GCP data services, especially BigQuery, Dataflow (Apache Beam), and Pub/Sub.
  • Experience building reliable batch and incremental pipelines for GA4/Google Ads data into BigQuery.
  • Experience with streaming patterns such as windowing, watermarks, and triggers for near-real-time processing.
  • Advanced proficiency in Looker Core and LookML, including derived tables, explores, and Liquid syntax.
  • Experience developing semantic models and dashboards for operational and executive audiences.
  • Ability to independently own workstreams while collaborating with data science, analytics, and engineering peers in agile delivery.
  • Advanced English skills.
  • Preferred: Google Cloud Professional Data Engineer certification, Google Professional Machine Learning Engineer certification, or Google Cloud Professional Cloud Architect certification.
  • Preferred: Bachelor’s or Master’s degree in a quantitative or technical field such as Computer Science, Engineering, or Statistics.
  • Preferred: Working knowledge of GCP cloud architecture components, Big Data tools such as Spark, Hive, Impala, and Pig, Terraform, front-end and back-end web stacks, API design and usage (REST/GraphQL), or experience leading technical data/analytics/machine learning projects.
  • Preferred: Experience supporting data products used by conversational analytics surfaces, including query routing, audit logging, and row-level access patterns.

Benefits

  • Growth opportunities and a values-driven culture.
  • International career opportunities.
  • A workplace culture that fosters creativity, diversity, and autonomy.
  • A borderless global framework that enables seamless collaboration.
  • Inclusive hiring and accommodations support during the interview process.

Interested in this position?

Apply directly on the company website

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