Celonis Data Engineer

London
1 week ago
Create job alert

Contract Opportunity: Data Engineer – Celonis Process Mining

📍 Location: Central London (Office Based)

📅 Start Date: ASAP

📄 Contract Length: 6 Months Initially

💷 Day Rate: TBC — expected around £500/day (Inside IR35)

About the Role

Our client is seeking a highly skilled Data Engineer with strong Celonis process mining expertise to join a leading financial services organisation. This role plays a pivotal part in enabling enterprise-wide process intelligence by transforming complex banking data into accurate, analysis‑ready insights.

Working within a regulated banking environment, you will design and deliver high‑quality event logs, build robust data pipelines, and optimise Celonis data models to support end‑to‑end visibility and drive operational improvement.

Key Responsibilities

  1. Data Engineering & Event Log Construction

  • Design, build, and maintain scalable event‑log pipelines for Celonis process mining.

  • Translate raw process event data (case IDs, activities, timestamps, attributes) into structured Celonis Data Models.

  • Ensure reusability, consistency, and performance across multiple processes.

  1. Data Model & Pipeline Development

  • Develop and optimise ETL/ELT pipelines from ERP and transactional banking systems.

  • Manage data ingestion, transformation, and refresh pipelines for Celonis datasets.

  • Build and fine‑tune Celonis CCPM and OCPM data models aligned to business requirements.

  • Work with large-volume transactional datasets while preserving end‑to‑end traceability.

  1. Performance, Quality & Assurance

  • Optimise SQL queries, transformations, and data models for performance at scale.

  • Conduct data validation, reconciliation, and root‑cause analysis.

  • Identify and resolve data quality issues proactively.

  1. Collaboration & Documentation

  • Partner closely with process analysts, functional teams, and business stakeholders.

  • Document data models, ETL logic, event log definitions, and technical decisions.

  • Support business users by enabling reliable, analysis‑ready datasets within Celonis.

  1. Governance & Best Practice

  • Ensure compliance with enterprise data governance, security, and audit standards.

  • Apply modern engineering best practices including version control, modular design, and pipeline monitoring.

  • Contribute to continuous improvement initiatives across the data engineering landscape.

    Your Profile

    Essential Skills

  • Proven experience in Celonis data engineering and process mining execution.

  • Hands‑on expertise with event log creation, Celonis data modelling (CCPM/OCPM), and PQL logic.

  • Strong proficiency in SQL, Python, ETL/ELT, and data modelling.

  • Experience handling high‑volume transactional datasets and performance optimisation.

    Desirable Skills

  • Understanding of process mining techniques and their analytics implications.

  • Strong documentation, analytical, and problem‑solving skills.

  • Background in banking or KYC operations is a plus.

    If you’re a data engineering professional with deep Celonis expertise and thrive in highly regulated environments, we’d love to hear from you.

    Apply now to start ASAP and play a critical role in transforming process intelligence within a major financial institution

Related Jobs

View all jobs

CELONIS PROCESS MINING - DATA ENGINEER

Data Engineer – Data Extraction & Warehouse Management

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.

New Data Science Employers to Watch in 2026: UK and International Companies Leading Analytics and AI Innovation

Data science has emerged as one of the most transformative forces across industries, turning raw information into actionable insights, predictive models, and AI-powered solutions. In 2026, the UK is witnessing a surge in organisations where data science is not just a support function but the core of their products and services. For professionals exploring opportunities on www.DataScience-Jobs.co.uk , identifying these employers early can provide a competitive advantage in a market with high demand for advanced analytics and machine learning expertise. This article highlights new and high-growth data science employers to watch in 2026, focusing on UK startups, scale-ups, and global firms expanding their data science operations locally. All of the companies included have recently raised investment, won high-profile contracts, or significantly scaled their analytics teams.

How Many Data Science Tools Do You Need to Know to Get a Data Science Job?

If you’re trying to break into data science — or progress your career — it can feel like you are drowning in names: Python, R, TensorFlow, PyTorch, SQL, Spark, AWS, Scikit-learn, Jupyter, Tableau, Power BI…the list just keeps going. With every job advert listing a different combination of tools, many applicants fall into a trap: they try to learn everything. The result? Long tool lists that sound impressive — but little depth to back them up. Here’s the straight-talk version most hiring managers won’t explicitly tell you: 👉 You don’t need to know every data science tool to get hired. 👉 You need to know the right ones — deeply — and know how to use them to solve real problems. Tools matter, but only in service of outcomes. So how many data science tools do you actually need to know to get a job? For most job seekers, the answer is not “27” — it’s more like 8–12, thoughtfully chosen and well understood. This guide explains what employers really value, which tools are core, which are role-specific, and how to focus your toolbox so your CV and interviews shine.

What Hiring Managers Look for First in Data Science Job Applications (UK Guide)

If you’re applying for data science roles in the UK, it’s crucial to understand what hiring managers focus on before they dive into your full CV. In competitive markets, recruiters and hiring managers often make their first decisions in the first 10–20 seconds of scanning an application — and in data science, there are specific signals they look for first. Data science isn’t just about coding or statistics — it’s about producing insights, shipping models, collaborating with teams, and solving real business problems. This guide helps you understand exactly what hiring managers look for first in data science applications — and how to structure your CV, portfolio and cover letter so you leap to the top of the shortlist.