Senior Technical Solutions Consultant, Data Engineering

Minimum qualifications:

Bachelor's degree or equivalent practical experience.

5 years of experience designing data pipelines, and dimensional data modeling for synch and asynch system integration and implementation using internal (e.g., Flume, etc.) and external stacks (DataFlow, Spark, etc.).

5 years of experience coding in one or more programming languages.

5 years of experience working with data infrastructure and data models by performing exploratory queries and scripts.

Preferred qualifications:

5 years of experience with statistical methodology and data consumption tools such as business intelligence tools, collabs, jupyter notebooks, Tableau, Power BI, DataStudio, and business intelligence platforms.

3 years of experience developing project plans and delivering projects on time within budget and scope.

3 years of experience partnering with stakeholders (e.g., users, partners, customer), and managing stakeholders/customers.

Experience with machine learning for production workflows.

About the job

As a Data Engineer supporting the Legal Content Policy and Standards team, you will drive technical solutions that help Google comply with global content regulations and protect user safety. You will take ownership of design and development initiatives for our data products and infrastructure. You will solve complex and ambiguous data problems. By building a unified data architecture, you will help reduce fragmentation and ensure consistent reporting. You will collaborate closely with policy leaders and engineering partners, defining data standards and guiding our technical roadmap to scale operations effectively.

Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

Ireland: €120000 - €123000 (EUR) + 15% bonus target + equity + benefits

Learn more about benefits at Google.

Responsibilities

Design, build, and maintain data processing systems and data structures that handle legal content removal and compliance reporting.

Collaborate with policy specialists and cross-functional partners to understand business needs and translate them into robust technical data designs.

Create unified data pipelines and models to simplify data access, reduce duplication, and establish clear sources of truth.

Analyze and profile large datasets to uncover trends, improve data quality, and enable data-driven operational decisions.

Guide engineering best practices for data lifecycle management, storage design, and data discoverability.