Business Intelligence Engineer

OpenSourced
1 month ago
Create job alert

We are recruiting for a forward-thinking company that is seeking aBusiness Intelligence Engineerto join their Engineering team. This role is pivotal in driving data-led initiatives to inform business decisions and optimise operations. The successful candidate will be responsible for identifying areas for system improvement, enhancing the company’s data infrastructure, and ensuring alignment with overall business objectives. You will also provide strategic insights and oversight to ensure data solutions support the company’s future growth.

Key Responsibilities

  1. Design, develop, and maintain data pipelines between business systems and the data warehouse.
  2. Build and optimisePower BIreporting solutions to meet evolving business needs.
  3. Monitor and troubleshoot data pipeline issues to ensure timely resolution.
  4. Manage version control of data components, ensuring robust governance of pipelines, reports, and integration processes.
  5. Conduct testing across all data pipeline components to ensure high-quality solutions.
  6. Be the key point of contact for all data solutions, ensuring the business has access to the data they need to make informed decisions.
  7. Apply modern cloud-first principles to design high-standard data solutions.
  8. Collaborate with the IT and business teams to support data function improvements, helping junior staff members and bridging technical knowledge gaps.
  9. Drive the delivery of data and business intelligence requirements across multiple projects.
  10. Work closely with business units to understand their data challenges and drive positive change in data-driven decision-making.
  11. Develop and implement data quality improvement roadmaps for core applications.
  12. Collaborate with internal IT teams (service desk, infrastructure, security, software engineers) to ensure smooth delivery of solutions.
  13. Proactively suggest and implement data quality improvements to drive business benefits.
  14. Manage sprints within agile project management guidelines to ensure timely delivery.
  15. Provide clear analysis, plans, and timescales for delivering key functionality across different departments.

Knowledge & Experience

The ideal candidate should have a strong technical background with experience in data engineering, software development, and business intelligence. They should have excellent SQL skills and be proficient in eitherPythonorNode.js(TypeScript). A deep understanding of database concepts, cloud infrastructure, and version control systems is essential. The candidate should also be experienced in designing and implementing ETL/ELT processes, developing data models, and supporting integrations from various data sources.

Requirements

  1. Strong experience withPythonorNode.js(TypeScript).
  2. Advanced SQL skills, with experience inRedshiftor OLAP systems preferred.
  3. Solid understanding of database concepts includingDDL,DML,DQL,TCL, andDCL.
  4. Query optimisation expertise and experience improving performance.
  5. Proficiency inLiquibaseand infrastructure as code (ideallyTerraform).
  6. Experience using version control systems likeGit/GitHuband familiarity with modern DevOps principles.
  7. Expertise in integrating data from various sources (e.g.REST APIs,SOAP APIs,S/FTP servers,GraphQL, webhooks).
  8. Experience withAWS serverless infrastructure(e.g. API Gateway, Lambda, SQS, SNS, Kinesis).
  9. Familiarity with ERP and financial systems, along with a basic understanding of financial processes (e.g. ledgers).
  10. Experience working in an agile environment and understanding agile project management principles.
  11. Excellent communication skills with the ability to explain complex technical concepts to non-technical stakeholders.
  12. Strong problem-solving skills and attention to detail.
  13. Knowledge of data modelling principles and relational database management systems.
  14. Technical leadership experience is highly desirable.

This is an excellent opportunity for aBusiness Intelligence Engineerlooking to take their career to the next level in a company committed to data-driven decision-making and innovation. If you're passionate about data, technology, and making an impact, we'd love to hear from you. Apply now!

#J-18808-Ljbffr

Related Jobs

View all jobs

Business Intelligence Engineer II, Amazon

Business Intelligence Engineer

Sr. Business Intelligence Engineer

BI Developer

Senior Data Engineer

Business Intelligence (PowerBI) Analyst & Developer

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.

Global vs. Local: Comparing the UK Data Science Job Market to International Landscapes

How to evaluate salaries, opportunities, and work culture in data science across the UK, the US, Europe, and Asia Data science has proven to be more than a passing trend; it is now a foundational pillar of modern decision-making in virtually every industry—from healthcare and finance to retail and entertainment. As the volume of data grows exponentially, organisations urgently need professionals who can transform raw information into actionable insights. This high demand has sparked a wave of new opportunities for data scientists worldwide. In this article, we’ll compare the UK data science job market to those in the United States, Europe, and Asia. We’ll explore hiring trends, salary benchmarks, and cultural nuances to help you decide whether to focus your career locally or consider opportunities overseas or in fully remote roles. Whether you’re a fresh graduate looking for your first data science position, an experienced data professional pivoting from analytics, or a software engineer eager to break into machine learning, understanding the global data science landscape can be a game-changer. By the end of this overview, you’ll be better equipped to navigate the expanding world of data science—knowing which skills and certifications matter most, how salaries differ between regions, and what to expect from distinct work cultures. Let’s dive in.

Data Science Leadership for Managers: Strategies to Motivate, Mentor, and Set Realistic Goals in Data-Driven Teams

Data science has become a linchpin in modern business, transforming oceans of raw data into actionable insights that guide strategy, product development, and personalised customer experiences. With this surge in data-centric operations, the need for effective data science leadership has never been more critical. Guiding a team of data scientists, analysts, and machine learning engineers requires not only technical acumen but also the ability to foster collaboration, champion ethical practices, and align complex modelling efforts with overarching business goals. This article provides practical guidance for managers and aspiring leaders aiming to excel in data-driven environments. By exploring strategies to motivate data science professionals, develop mentoring frameworks, and set achievable milestones, you will be better prepared to steer your team towards meaningful, evidence-based outcomes.

10 Essential Books to Read to Nail Your Data Science Career in the UK

Data science continues to be one of the most exciting and rapidly evolving fields in tech. With industries across the UK—ranging from finance and healthcare to e-commerce and government—embracing data-driven decision-making, the demand for skilled data scientists has soared. Whether you're a recent graduate looking for your first role or a professional aiming to advance your career, staying updated through books is crucial. In this article, we explore ten essential books every data science job seeker in the UK should read. Each book provides valuable insights into core concepts, practical applications, and industry-standard tools, helping you build skills employers are actively looking for.