Senior Data Governance Engineer

Elanco
Lower Basildon
1 month ago
Applications closed

Related Jobs

View all jobs

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer

Senior Data Services Manager

Senior Data Services Manager

Senior Data Architect

At Elanco (NYSE: ELAN) – it all starts with animals! As a global leader in animal health, we are dedicated to innovation and delivering products and services to prevent and treat disease in farm animals and pets.
We’re driven by our vision of ‘Food and Companionship Enriching Life’ and our approach to sustainability – the Elanco Healthy Purpose™ – to advance the health of animals, people, the planet and our enterprise. At Elanco, we pride ourselves on fostering a diverse and inclusive work environment.
We believe that diversity is the driving force behind innovation, creativity, and overall business success.
Here, you’ll be part of a company that values and champions new ways of thinking, work with dynamic individuals, and acquire new skills and experiences that will propel your career to new heights. Making animals’ lives better makes life better – join our team today! Location: Hook, UK (Hybrid) Data Engineering at Elanco is growing across ingestion, integration, transformation, consumption, and governance capabilities to deliver data products that will transform how the organization leverages data.
The Data Engineering and Platforms organization is seeking an experienced Data Governance Engineer to provide technical leadership to both internal and partner teams working within our Enterprise Data environment.
This is a broad role which will include coaching and leading junior engineers in their domain, as well as partnering with engineering and product leadership to deliver on the data strategy. To be successful in an engineering role at Elanco requires a highly motivated individual with an innovative mindset and willingness to drive tangible outcomes.
The individual must be able to articulate complex technical topics, collaborate with internal and external partners, and ensure quality delivery of the required data products. Reporting to the Associate Director - Data Platforms, the Lead Data Governance Engineer will manage all technical aspects of the Collibra Data Intelligence Platform ecosystem, including platform administration, release management, security, system integrations, and optimization of core components (Console, DIC, Edge, Lineage Harvester, and DQ&O).
This role requires expertise in cloud computing, data management, and platform automation, with specific knowledge of Databricks, MS Azure, Terraform, and API integration.
As part of a global, cross-functional team of technology and data experts, this role collaborates globally to ensure the platform's successful implementation and adoption. Responsibilities Platform Administration * Administer and maintain the Collibra Data Governance platform including Collibra Console, Collibra DIC, Edge, Lineage Harvester and Collibra Data quality & observability. * Working in terminals with Shell commands to manage the platform and VMs. * Work with data engineers to facilitate data integration to systems such as Databricks, Azure Synapse, Power BI, & GCP Big query. * Configure and manage Collibra communities/domain, workflows, data lineage, and business glossaries. * Work with business SMEs and identified project partners to develop requirements (functional/non-functional/operational/data quality) for Data Governance, Metadata, Data Quality and translate them into technical solutions. * Collaborate with data stewards, data owners, and IT teams to ensure data governance policies and standards are effectively implemented. * Manage licenses and users including role-based access control. * Responsible for user/ user group onboarding on Collibra with correct privileges, including advising on right privileges to manage security and license cost optimization. * Develop training materials, use case and asset model documentation, as well as implementation specification. * Provide recommendations for leveraging full functionality of Collibra platform (workflow, lineage diagrams, UI, dashboards, views, etc.). * Manage server configurations, monitor system performance, and troubleshoot issues. * Work closely with Data governance product owner, the Enterprise data office, IT, and data engineering teams to understand requirements, gather feedback, and continuously improve platform performance and user experience.   DevOps and Automation * Integrate Collibra with other enterprise systems, infrastructure automation, and tools using APIs, Kubernetes, Terraform, and Ansible for CI/CD and IaC.   Continuous Learning * Provide technical support and training to users on the Collibra platform and related tools. * Stay ahead of Collibra updates, big data technologies, automation tools, and cloud services. * Recommend and implement best practices for data governance, automation, and platform management. Qualifications * Bachelor’s Degree in Computer Science, Software Engineering, or equivalent professional experience. * 4+ years of experience engineering and delivering enterprise scale data solutions, with examples in the cloud (especially Databricks, Azure, and GCP) strongly preferred. * 4+ years of experience administering a Data governance platform, ideally Collibra. Additional Skills/Preferences * Collibra Ranger or Solution Architect certification. * Ability to translate complex business needs into technical requirements. * Experience with Infrastructure automation and application techniques and technologies such as Terraform, Kubernetes, and Ansible. * Strong proficiency in administration, configuration, functional & technical architecture of Collibra across Collibra Data intelligence Cloud, Lineage Harvester, Collibra Edge and Collibra Data Quality & Observability. * Experience with ETL tools and processes, ensuring proper data lineage and data quality. * Experience with APIs for system integration and process automation. * Experience with Collibra Data Quality tools for data profiling and data quality rule implementation. * Familiarity with data tools and cloud platforms such as Power BI, Azure, Databricks, GCP, and Big Query. * Experience configuring and customizing workflows in Collibra using Business Process Model and Notation (BPMN). * Solid understanding of data governance principles, lineage, and metadata management. * Exceptional problem-solving, proactiveness, and attention to detail. * Strong communication, collaboration, and the ability to work effectively across teams. * Experience working in complex enterprise landscapes (business, technology, regulatory, partners, providers, geographies, etc.). Other Information: Occasional travel may be required. Direct Reports: 0 Elanco is an EEO/Affirmative Action Employer and does not discriminate on the basis of age, race, color, religion, gender, sexual orientation, gender identity, gender expression, national origin, protected veteran status, disability or any other legally protected status

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Navigating Machine Learning Career Fairs Like a Pro: Preparing Your Pitch, Questions to Ask, and Follow-Up Strategies to Stand Out

Machine learning (ML) has swiftly become one of the most in-demand skill areas across industries, with companies leveraging predictive models and data-driven insights to solve challenges in healthcare, finance, retail, manufacturing, and beyond. Whether you’re an early-career data scientist aiming to break into ML, a seasoned engineer branching into deep learning, or a product manager exploring AI-driven solutions, machine learning career fairs offer a powerful route to connect with prospective employers face-to-face. Attending these events can help you: Network with hiring managers and technical leads who make direct recruitment decisions. Gain insider insights on the latest ML trends and tools. Learn about emerging job roles and new industry verticals adopting machine learning. Showcase your interpersonal and communication skills, both of which are increasingly important in collaborative AI/ML environments. However, with many applicants vying for attention in a bustling hall, standing out isn’t always easy. In this detailed guide, we’ll walk you through how to prepare meticulously, pitch yourself confidently, ask relevant questions, and follow up effectively to land the machine learning opportunity that aligns with your ambitions.

Common Pitfalls Machine Learning Job Seekers Face and How to Avoid Them

Machine learning has emerged as one of the most sought-after fields in technology, with companies across industries—from retail and healthcare to finance and manufacturing—embracing data-driven solutions at an unprecedented pace. In the UK, the demand for skilled ML professionals continues to soar, and opportunities in this domain are abundant. Yet, amid this growing market, competition for machine learning jobs can be fierce. Prospective employers set a high bar: they seek candidates with not just theoretical understanding, but also strong practical skills, business sense, and an aptitude for effective communication. Whether you’re a recent graduate, a data scientist transitioning into machine learning, or a seasoned developer pivoting your career, it’s essential to avoid common mistakes that may hinder your prospects. This blog post explores the pitfalls frequently encountered by machine learning job seekers, and offers actionable guidance on how to steer clear of them. If you’re looking for roles in this thriving sector, don’t forget to check out Machine Learning Jobs for the latest vacancies across the UK. In this article, we’ll break down these pitfalls to help you refine your approach in applications, interviews, and career development. By taking on board these insights, you can significantly enhance your employability, stand out from the competition, and secure a rewarding position in the world of machine learning.

Career Paths in Machine Learning: From Entry-Level Roles to Leadership and Beyond

Machine learning has rapidly transformed from an academic pursuit to a cornerstone of modern technology, fueling innovations in healthcare, finance, retail, cybersecurity, and virtually every industry imaginable. From predictive analytics and computer vision to deep learning models that power personalisation algorithms, machine learning (ML) is reshaping business strategies and creating new economic opportunities. As demand for ML expertise continues to outstrip supply, the UK has become a vibrant hub for machine learning research, entrepreneurship, and corporate adoption. Whether you’re just starting out or have experience in data science, software development, or adjacent fields, there has never been a better time to pursue a career in machine learning. In this article, we will explore: The growing importance of machine learning in the UK Entry-level roles that can kick-start your ML career The skills and qualifications you’ll need to succeed Mid-level and advanced positions, including leadership tracks Tips for job seekers on www.machinelearningjobs.co.uk By the end, you’ll have a clear view of how to build, grow, and lead in one of the most exciting fields in modern technology.