Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Boomi Expert / Developer

Finatal
London
11 months ago
Applications closed

Related Jobs

View all jobs

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Job Title: Boomi Expert / Developer

Location: London (Hybrid)

Type: Contract (Outside IR35)

Start Date: Immediate


EM001


About Us:

We are a fast-growing SaaS business, backed by Private Equity, on a mission to transform data-driven decision-making across our industry. We leverage cutting-edge tools and platforms to create seamless, integrated solutions that drive value for our clients. Join us as we expand our data infrastructure and analytics capabilities to support our rapid growth trajectory.


Position Overview:

We are seeking aBoomi Expert / Developerto build and optimize data pipelines for our organization. This role is crucial to ensuring our data flows smoothly and accurately across systems, facilitating insights and analysis across multiple departments. You will work with stakeholders to create and manage data pipelines from platforms like ServiceNow and Dynamics into Snowflake, monitor for data integrity, set up alerts, and support ERP data migrations. This is an exciting opportunity for a hands-on data integration expert looking to make a meaningful impact in a dynamic SaaS environment.


Key Responsibilities:

  • Data Pipeline Development:Design, build, and maintain data pipelines, including integrations between ServiceNow, Dynamics, and Snowflake.
  • Data Extraction & Transformation:Extract, clean, and transform data from Snowflake to support analytics and reporting.
  • Alerting & Monitoring:Set up alerts, notifications, and health checks on all data pipelines to ensure timely troubleshooting and resolution.
  • ERP Data Migration:Collaborate with IT and other teams to support migration and integration of data from ERP systems.
  • Data Quality Assurance:Ensure high levels of data quality, integrity, and accuracy across data flows.
  • Collaboration & Documentation:Work closely with data analysts, IT, and business stakeholders to understand requirements and document workflows.


Skills & Experience:

  • Boomi Expertise: Proven experience building and managing data integrations using the Boomi platform.
  • ETL & Data Integration:Strong background in ETL processes, particularly in connecting ServiceNow, Dynamics, and Snowflake.
  • Snowflake Proficiency:Demonstrated ability in extracting, cleaning, and transforming data within Snowflake.
  • Alerting & Monitoring:Experience setting up and managing alerts and notifications for data pipelines.
  • ERP Migration:Prior experience with ERP data migrations is a strong advantage.
  • PE-backed Experience: Experience working for Private Equity-backed companies is highly desirable.
  • Problem-Solving & Communication:Strong analytical, problem-solving, and communication skills, with a collaborative approach.


Why Join Us?

  • Opportunity to make a significant impact in a high-growth SaaS company.
  • Collaborative, innovative, and dynamic work environment.
  • Competitive compensation and benefits.


If you are a proactive Boomi expert ready for a new challenge and an immediate start, we would love to hear from you. Apply now to join our team and make an impact!

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

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

Industry Insights

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

Data Science Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK data science hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise rigorous problem framing, high‑quality analytics & modelling, experiment/causality, production awareness (MLOps), governance/ethics, and measurable product or commercial impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for product/data scientists, applied ML scientists, decision scientists, econometricians, growth/marketing analysts, and ML‑adjacent data scientists supporting LLM/AI products. Who this is for: Product/decision/data scientists, applied ML scientists, econometrics & causal inference specialists, experimentation leads, analytics engineers crossing into DS, ML generalists with strong statistics, and data scientists collaborating with platform/MLOps teams in the UK.

Why Data Science Careers in the UK Are Becoming More Multidisciplinary

Data science once meant advanced statistics, machine learning models and coding in Python or R. In the UK today, it has become one of the most in-demand professions across sectors — from healthcare to finance, retail to government. But as the field matures, employers now expect more than technical modelling skills. Modern data science is multidisciplinary. It requires not just coding and algorithms, but also legal knowledge, ethical reasoning, psychological insight, linguistic clarity and human-centred design. Data scientists are expected to interpret, communicate and apply data responsibly, with awareness of law, human behaviour and accessibility. In this article, we’ll explore why data science careers in the UK are becoming more multidisciplinary, how these five disciplines intersect with data science, and what job-seekers & employers need to know to succeed in this transformed field.

Data Science Team Structures Explained: Who Does What in a Modern Data Science Department

Data science is one of the most in-demand, dynamic, and multidisciplinary areas in the UK tech and business landscape. Organisations from finance, retail, health, government, and beyond are using data to drive decisions, automate processes, personalise services, predict trends, detect fraud, and more. To do that well, companies don’t just need good data scientists; they need teams with clearly defined roles, responsibilities, workflows, collaboration, and governance. If you're aiming for a role in data science or recruiting for one, understanding the structure of a data science department—and who does what—can make all the difference. This article breaks down the key roles, how they interact across the lifecycle of a data science project, what skills and qualifications are typical in the UK, expected salary ranges, challenges, trends, and how to build or grow an effective team.