Data Engineer
Role details
Job location
Tech stack
Job description
As the Data Engineer, you will play a pivotal role in shaping and delivering our data strategy to drive business insights, enhance operational efficiency, and support strategic decision-making. You will be working within a dynamic team of data professionals and collaborating with cross-functional departments to leverage data as a strategic asset.
Passionate and motivated people are the power behind our growth so we're looking to expand our team and you could be part of our success story.
What We Need from Yü
Data Strategy and Governance
- Uphold and deliver data strategy aligned with business goals and industry best practices.
- Enforce data governance policies and procedures to ensure data quality, integrity, and security.
Data Privacy and Compliance
- Ensure data compliance and security needs are met in system construction and access control.
- Apply security measures such as RLS and Column Masking to keep the data secure to the correct parties.
Data Engineering
- Design, build, and optimise scalable data solutions using Snowflake, Azure Data Services, and DBT for data transformation and modelling.
- Support the Head of Data in managing the project prioritisation, identifying any potential threats to delivery.
- Optimise and validate performance and cost of data workloads within Snowflake (query tuning) and Azure environments.
Data Sourcing & Pipeline Management
- Use programming language to maintain data sets, databases, tables, data lakes or data warehouses.
- Implement big data tools such as Apache Spark / Kafka to automate data pipelines.
- Develop connections between multiple sources of data with APIs or database connectors
Collaboration
- Work closely with cross-functional teams, including IT, finance, marketing, and operations, to understand their data needs and provide strategic guidance.
- Collaborate with the Senior Data Engineer, Data Engineers and Data Analysts to determine design needs.
Performance Metrics
- Contribute to the Key Performance Indicators (KPIs) related to data quality, analytics, and business impact., We have a wide range of benefits for our employees including:
- 24 Days Annual Leave + 1 Day Birthday Leave + Bank Holidays
- Holiday Buy - up to 5 additional day
- Employee Assistance Programme
- Annual Salary Review
- Learning and development opportunities
- Enhanced paternity, maternity and adoption policies
- Yü made a difference Awards.
- 3 days additional annual leave if you get married/civil partnership etc.
- Appointment allowance
- Long service recognition
- Refer a friend payment.
- Company sick pay (subject to length of service)
- New modern facilities
- Death in service and critical illness cover
- Plus, many more
Requirements
Do you have experience in Spark?, * Degree educated or 2+ years' experience in data engineering, data system development or related roles.
- Ability to build, maintain and improve upon data architecture, collection and storage systems.
- Fundamental understanding of core data engineering practices, metadata and SCD application.
- Proficiency in data warehousing (including the Lakehouse concept), relational databases and ETL.
- Ability to build and maintain data architectures, pipelines and sets.
- Working knowledge of key programming languages such with preference in machine learning
- Experience working with Apache Spark, Python, SQL and similar tools / programs.
- Experience working with modern cloud solutions such as Snowflake, Databricks, Fabric preferable.
- Strong knowledge of data governance, architecture, analytics, and emerging technologies.
- Excellent communication skills with the ability to convey technical concepts to non-technical stakeholders.
- Familiarity with regulatory requirements, especially in the of data protection and privacy.
- Strong understanding of the energy industry and related data challenges or ability to adapt and learn new information effectively and efficiently.