[Hiring] Senior Analytics Engineer @Accesa

Role Description

We are hiring for a major customer and looking for a Senior Analytics Engineer to join a large-scale data platform modernization initiative in the Google Cloud ecosystem, supporting the migration of enterprise data warehouse workloads from Teradata to BigQuery. In this role, you will discover and manage the central Common Data Model (CDM) hub, support the creation of new data spokes for consuming teams, and build a deep understanding of the data model and business KPIs to ensure they are implemented consistently and used correctly across the platform.

Responsibilities

• Build and maintain data pipelines:
  • Design, develop, and optimize scalable data transformation pipelines in BigQuery using Dataform and SQL, ensuring reliability and performance.
• Drive data warehouse migration:
  • Support the transition from Teradata to BigQuery by analyzing, translating, and validating existing data models and logic.
• Own the Common Data Model:
  • Discover, document, and manage the CDM hub, ensuring consistency, governance, and seamless data consumption across teams.
• Enable data platform adoption:
  • Support the onboarding of new CDM consumers, providing guidance on data model usage and integration best practices.
• Align data with business goals:
  • Analyze business KPIs and ensure their definitions, calculations, and usage are accurately reflected in the data model.
• Act as a data model expert:
  • Maintain deep knowledge of data structures, lineage, and semantics, serving as a key reference point for stakeholders.
• Ensure data quality and trust:
  • Drive testing, validation, and reconciliation activities across Teradata and BigQuery environments to guarantee data accuracy.
• Optimize platform performance:
  • Improve BigQuery workloads for performance, cost efficiency, and long-term maintainability.
• Promote engineering standards:
  • Contribute to documentation, modeling standards, and best practices that strengthen the overall data platform.
• Collaborate across teams:
  • Partner with engineers, analysts, architects, and business stakeholders to deliver trusted and well-understood data products.

Qualifications

• Must Have
  • Professional experience as an Analytics Engineer, Data Engineer, or BI Engineer, with a senior level of ownership and autonomy.
  • Strong, hands-on SQL expertise, including complex transformations, analytical queries, and performance optimization.
  • Practical experience with Google Cloud Platform, in particular BigQuery.
  • Hands-on experience with Dataform (or a similar SQL-based transformation framework such as dbt, with the willingness to work with Dataform).
  • Solid understanding of data modeling concepts (dimensional modeling, layered architectures, hub-and-spoke / common data model approaches).
  • Ability to understand business KPIs and translate their definitions and usage into correct, maintainable data model implementations.
  • Experience ensuring data quality through testing, validation, and reconciliation of datasets.
  • Regular use of AI tools to improve productivity, automate or reduce repetitive work, support decision-making, and deliver higher-quality outcomes.
  • Ability to use AI tools responsibly by structuring effective prompts, critically validating outputs, understanding limitations, and taking ownership of the final result.
  • Excellent English communication skills, including the ability to communicate design decisions to technical and non-technical stakeholders, and to thrive in a fast-paced, agile environment.
• Nice to Have
  • Hands-on experience with Teradata (Teradata SQL, BTEQ) or with Teradata-to-BigQuery migration projects.
  • Experience with Python for data processing, automation, or tooling.
  • Experience with other GCP data services (Cloud Composer / Airflow, Dataflow, Pub/Sub, Cloud Storage, Dataplex).
  • Familiarity with BI and reporting tools (e.g., Looker, Power BI, Tableau) and how KPIs are consumed downstream.
  • Exposure to data governance, data cataloging, or lineage practices and tooling.
  • Familiarity with CI/CD and infrastructure-as-code practices applied to data pipelines.
  • Google Cloud certification (e.g., Professional Data Engineer).

Benefits

• Enjoy our holistic benefits program that covers the four pillars that we believe come together to support our wellbeing, covering social, physical, emotional wellbeing, as well as work-life fusion.
• Physical Wellbeing: Our wellbeing program includes medical benefits, gym support, and personalised fitness options for an active lifestyle, complemented by team events and the Healthy Habits Club.
• Work-Life Fusion: In very dynamic industries such as IT, the line between our professional and personal lives can quickly become blurred. Having a one-size-fits-one approach gives us the flexibility to define the work-life dynamic that works for us.
• Emotional Wellbeing: We believe that to maintain our overall health, we need to invest in our mental wellbeing just as much as we do in our physical health, social connections or in achieving work-life balance.
• Social Wellbeing: As a growing community in a hybrid environment, we want to ensure we remain connected not just by the great work we do every day but through our passions and interests.