Senior Data Scientist

CompanyGlobalLogic

LocationLondon Area, United Kingdom

Posted At11/21/2025

UK Visa Sponsorship Analytics

Occupation Type

Actuaries, economists and statisticians

Occupation Code Skill LevelHigher Skilled

Sponsorship Salary Threshold

£55,100 (£28.26 per hour)

Occupation rate applies

Above analytics are generated algorithmically based on job titles and may not always be the same as the company's job classification. You can also check detailed occupation eligibility, and salary criteria on our UK Visa Eligible Occupations & Salary Thresholds page.

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Description

This is a senior leadership position where you'll drive business transformation through data, from developing strategic roadmaps to delivering complex, large-scale architectures. You are a leader in data and IT consulting with a proven track record of delivering business value. You are comfortable in high-stakes, business-critical environments and have a natural ability to attract trust at a board level. Your passion for innovative data solutions is matched by your technical depth and ability to simplify complex concepts for diverse audiences.

Responsibilities

Success at GlobalLogic is built on strong core competencies. We seek a professional who excels in:
Driving outcomes through influencing, decision-making, and negotiation.
Proactively engaging clients and stakeholders to deliver high-value solutions, nurturing relationships, and providing/receiving candid feedback.
Excelling at stakeholder management, relationship building, active listening, and client empathy to understand needs.
Confidently conveying complex information with exceptional communication and presentation skills, using emotional intelligence to resolve conflict constructively.
Possessing strong business acumen to link technical solutions to strategic value.
Demonstrating high resilience and adaptability, effectively managing competing priorities, and championing continual learning.

Additionally, you will:

Define data architecture vision, strategy, and roadmaps with C-level and board-level stakeholders, leading strategic IT/business transformations.
Architect scalable data processing and analytics solutions, including enterprise data lakes and data warehouses, and lead business architecture solutions across cloud and associated technologies.
Hands-on develop and implement data solutions, design robust data pipelines for machine learning and business intelligence, and integrate various data sources.
Interface with clients to understand their needs, communicate data-driven insights, foster trust, and provide subject matter expertise for proposals and RFPs.

Requirements

Cloud Data Architecture: Proven hands-on experience designing and implementing cloud-native data platforms, with deep expertise in AWS, GCP, or Azure. Must be proficient in modern services such as Amazon EMR, Redshift, Athena, Glue, Lambda, BigQuery, and Google Dataflow.
Experience with cloud data warehouses (e.g., Snowflake, Databricks) is highly desirable.
Modern Data Engineering Frameworks: Advanced proficiency in big data ecosystems—Hadoop, Spark (including PySpark), Flink, and contemporary MLOps or DataOps tooling (Airflow, dbt, Prefect).
Database Expertise: Strong command of both traditional (SQL Server, Oracle, PostgreSQL, MySQL) and modern NoSQL platforms (MongoDB, Cassandra, DynamoDB, Cosmos DB).
Data Visualisation & Analytics: Familiarity with leading BI platforms (PowerBI, Tableau, Qlik). Experience integrating with embedded analytics and self-service data models is a plus.
Programming & Automation: Strong coding skills in Python, with hands-on experience in R and/or Scala. Proficiency in infrastructure-as-code using Terraform, CloudFormation, or Pulumi. Experience integrating CI/CD pipelines and deploying containerised solutions (Docker, Kubernetes).
Agile & Architecture Standards: Experience working within Agile and DevOps environments. Skilled in applying architectural frameworks such as TOGAF, Zachman, or the Data Management Body of Knowledge (DMBOK).
Data Modelling & Pipeline Design: Expertise in conceptual/logical/physical data modelling, metadata management, building robust ETL/ELT pipelines, event streaming (Kafka, Kinesis, Pub/Sub), and supporting cloud and hybrid data migrations.
Data Governance & Compliance: Deep understanding of data protection, privacy, and governance frameworks (GDPR, CCPA, ISO 27001, DAMA). Experience implementing data quality, auditing, cataloging (DataHub, Collibra, Alation, Open Metadata), and master data management capabilities.
Emerging Technology Awareness: Familiarity or hands-on exposure to AI/ML integration, knowledge graphs, data mesh/data fabric architectures, and observability tooling (e.g., Monte Carlo, DataDog, OpenLineage).
Strong Communication & Leadership: Excellent stakeholder engagement, requirements gathering, and technical leadership skills. Proven ability to bridge business needs and technical execution.