Data Engineer
Equiniti is a leading international provider of shareholder, pension, remediation, and credit technology. With over 6000 employees, it supports 37 million people in 120 countries.
EQ’s vision is to be the leading global share registrar, offering complementary services to its client base and our values set the core foundations to our success. We are TRUSTED to deliver on our commitments, COMMERCIAL in building long term value, COLLABORATIVE in our approach and we IMPROVE by continually enhancing our skills and services. There has never been a better time to join EQ.
Role Summary
EQ’s Global IT function has begun a transformation journey to support EQ’s transition into a stronger, more profitable, product-led business, driven by real insights and the needs of its customers.
We are looking for a skilled Data Engineer to join our Data team. As a Data Engineer, you will be responsible for designing, building, and maintaining large-scale data pipelines using Microsoft Fabric and Databricks. You will work closely with our Product and Engineering teams to ensure data flow and integration across our data ecosystem. Your expertise will help us to improve our data infrastructure, improve data quality, and enable data-driven decision-making across the organization.
Core Duties and Responsibilities
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Design, build, and maintain large-scale data pipelines using Microsoft Fabric and Databricks
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Develop and implement data architectures that meet business requirements and ensure data quality, security, and compliance
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Collaborate with wider Product & Engineering teams to integrate data pipelines with machine learning models and analytics tools
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Optimise data processing and storage solutions for performance, scalability, and cost-effectiveness
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Develop and maintain data quality checks and monitoring tools to ensure data accuracy and integrity
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Work with cross-functional teams to identify and prioritize data engineering projects and initiatives
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Stay up-to-date with industry trends and emerging technologies in data engineering and cloud computing
Skills Capabilities and Attributes
Essential:
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Good experience in data engineering, with a focus on cloud-based data pipelines and architectures
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Experience in Microsoft Fabric and Databricks, including data pipeline development, data warehousing, and data lake management
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Proficiency in Python, SQL, Scala, or Java
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Experience with data processing frameworks such as Apache Spark, Apache Beam, or Azure Data Factory
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Strong understanding of data architecture principles, data modelling, and data governance
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Experience with cloud-based data platforms, including Azure and or AWS
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Strong collaboration and communication skills, with the ability to work effectively with cross-functional teams
Desirable:
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Experience with Azure Synapse Analytics, Azure Data Lake Storage, or other Azure data services
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Experience with agile development methodologies and version control systems such as Git
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Certification in Microsoft Azure, Databricks, or other relevant technologies
