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Data Engineer

Tottenham Hotspur

Tottenham Hotspur is a world-famous football club based in London. On the pitch, the Club competes in the upper echelons of the English Premier League and is a regular participant in marque UEFA club competitions.

Posted
9 May 2024
Status
Full Time
Location
England
Closing date
22 May 2024

The Football Insights Department provides data-derived insights that impact decision-making across football departments, from the First Team to the Academy and including both Men's and Women's teams. Our mission is ensuring that critical processes, from player recruitment to performance optimisation, are consistently informed by thorough, high-quality information. With a focus on building a single source of truth, developing rigorous quantitative models, and delivering effective tools for interrogating data, our intention is to empower stakeholders with insightful statistical analyses that are both timely and actionable. Leveraging data as our fundamental commodity and powered by talent, we are looking to push the cutting edge of football analytics to drive the club towards its ambitious footballing vision.

Job Purpose

  • To develop and maintain robust, scalable data infrastructure and ETL pipelines that underpin the club's analytics platform, ensuring data from diverse sources is accurately ingested, processed, and made readily available for analysis across all football departments.
  • To continually enhance our technical infrastructure through innovative engineering solutions, focusing on the scalability and reliability of systems that support the club’s data platforms, ensuring they are well-integrated and capable of handling evolving analytical demands.
  • To collaborate effectively with Data Scientists and Analysts to support the production and integration of advanced machine learning models, facilitating the seamless transition of bespoke metrics into insights on player and team performance.

Key Responsibilities

  • Automate data processes to streamline club operations, identifying and addressing bottlenecks to improve data throughput and quality.
  • Design, develop, and maintain scalable ETL pipelines and data architectures to ensure data accuracy, quality, and security across internal and external sources.
  • Ingest data from heterogenous sources and build validations to assess data quality.
  • Manage data transformation across multiple layers and incorporate data modelling for analytical purposes (e.g., dimensional, and semantic), ensuring data is accurately processed, validated, and enriched to meet analytical requirements and support decision-making processes.
  • Collaborate closely with Data Scientists to productionise machine learning models, integrating bespoke metrics into cleaned and merged datasets to drive strategic insights.
  • Implement and maintain CI/CD pipelines for testing, deployment, and version control in tools like dbt, ensuring the consistent application of best practices in code management.
  • Collaborate with the club's Technology Department to leverage and evolve a modern tech stack, ensuring the seamless integration of data analytics capabilities with the club's broader technological infrastructure.
  • Provide prompt support for time-sensitive data infrastructure issues, ensuring operational continuity during critical periods like match analysis cycles.
  • Uphold our technical best practices and standards, mentoring staff on good programming practices and coding literacy.
  • Maintain rigorous documentation practices to ensure clarity, accuracy, and consistency in data management and pipeline development.
  • Manage key relationships with data vendors and technology partners, ensuring access to timely and relevant data that supports the club’s processes.
  • Contribute to the expansion of the Football Insights department by identifying areas for growth and shaping its future direction and capabilities.
  • Play a pivotal role in the recruitment and onboarding process for data/analytics engineering talent, from identifying potential candidates to advising on hiring decisions, with a focus on building a diverse and skilled team.

Person Specification

Skills and Competencies

Essential

  • Master’s or higher degree in a quantitative field (Mathematics, Statistics, Computer Science, or related fields) or equivalent experience working in the software/data industry.
  • 3+ years as a Data/Analytics/Infrastructure/ML Engineer or combined experience with a similar role in the data industry (e.g., Data Scientist).
  • Advanced proficiency in statistical programming languages, especially Python and/or R.
  • Proficient in SQL development and knowledgeable about database and data warehousing technologies.
  • Solid experience with cloud services from major providers (e.g., Azure, AWS, Google Cloud), with a comprehensive understanding of cloud-based data solutions and best practices.
  • Experience with major data warehousing solutions (e.g., Snowflake, BigQuery, Redshift), including their architecture and data modelling capabilities.
  • Proficiency in implementing and managing medallion architecture within cloud data platforms, demonstrating a strong understanding of layer segregation from raw to validated and enriched stages.
  • Extensive experience in integrating diverse data sources using APIs.
  • Experience processing and storing large “out-of-memory” datasets, e.g. using distributed data processing technologies (e.g. Apache Spark) and columnar storage formats.
  • Ability to communicate effectively and with a high degree of empathy to elicit requirements and deliver solutions to stakeholders who may have varying technical backgrounds.

Desirable

  • In-depth knowledge of Azure's cloud services and architecture.
  • Experience with Azure Data Factory (ADF) for data ingestion and workflow orchestration.
  • Proficiency in Blob Storage for data storage solutions.
  • Experience using dbt (Data Build Tool) for SQL-based data transformation and modelling.
  • Experience with Snowflake for data warehousing, including its architecture and data modelling capabilities.
  • Strong foundations in software engineering best practices, including version control (e.g., Git), automated testing, and CI/CD processes.
  • Broad working knowledge of BI tools, preferably Tableau, to support analytics use cases.
  • Experience with football data providers, specifically StatsBomb and SkillCorner, for advanced data analysis.

Personal Attributes

  • Passionate about football, with a keen appreciation for the dynamics and pace of elite sports.
  • Demonstrates innovative thinking and exceptional problem-solving skills, consistently pushing the boundaries in data engineering practices.
  • A collaborative team player, committed to building effective relationships and achieving collective success within a multidisciplinary team.
  • Possesses a growth mindset, actively seeking to enhance personal skills and stay updated with the latest advancements in data engineering.
  • Proactively manages project timelines and workload, especially during critical periods of the football season, ensuring timely delivery of solutions.
  • Ambitious and competitive, striving to leverage cutting-edge data engineering techniques to give the club a competitive advantage on and off the pitch.

How to Apply

Please click “Apply Now” to begin your application.


Additional Information

Status
Full Time
Job Type
Sports Technology
Sport
Football
Pay Information
Competitive

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