Senior Implementations Data Engineer

Altana
London
3 months ago
Applications closed

Related Jobs

View all jobs

Senior Data Engineer

Senior Data Engineer

Data Engineer - (Python, SQL, Machine Learning) - Robotics

Data Engineer Snowflake,DBT, Asset Management

P2P Business Data Analyst hybrid

Data Analyst – Demand Planning & Supply Chain

Altana is the network for trusted trade. Our AI-powered product network empowers governments and businesses to build a more resilient and secure global economy while keeping trade flowing.

The Opportunity at Altana

The Implementation team is focused on integrating Altana’s products with customers to provide unique insights, business process integrations, and create mutual value. We execute complex customer integrations to create and customize data pipelines for unique customer scenarios; integrate proprietary customer data to our knowledge graph while preserving privacy. The Implementation team works closely with customers, as well as our internal engineering, machine learning, and product organizations.

Specifically, The Team Is Focussed On

  • Develop, deploy and continuously improve distributed, big-data pipelines powering Altana’s state of the art network analysis, ML, data ingestion and fusion capabilities
  • Understanding and driving forward Altana's technology to make it more scalable and to meet the evolving requirements of our customer base
  • Serve as the technical expert in client-facing meetings, bridging the gap between complex government requirements and our platform's technical architecture.
  • Work in a cross-functional team of engineers, data scientists, and product managers
  • Evaluate and recommend new tools, technologies, and best practices for data pipeline development, orchestration and deployment

About You

You are a data engineer with a strong technical background who excels at building trust and communicating complex technical concepts to stakeholders. You are someone who proactively takes ownership of the end-to-end design and operation of data solutions and refines the systems to deliver measurable results.

  • You will have worked across design, development, and maintenance of data models from a variety of sources and schemas
  • Experience across the full lifecycle (Design, Development, Test, Deploy, Monitor, Maintain) of data ingestion and standardization pipelines.
  • A demonstrated drive for sustainable software development, self-healing data workflows, and a deep appreciation for data security and data governance.
  • Excellent written and verbal communication skills, with a track record of successfully interacting directly with external customers and stakeholders to scope technical work and manage expectations.
  • You are eligible and willing to obtain UK Security Check (SC) clearance or have an active clearance already
  • 5 years+ technical experience in data engineering or closely related roles
  • Keep up to date with latest trends in data engineering and care deeply about engineering excellence and knowledge sharing

Nice To Have, But Not Required

  • Expertise or experience with the deployment of ML pipelines.
  • Exposure to trade compliance, supply chain management or a field similarly related to international commerce.
  • Experience working with or within public sector.
  • Experience with the responsibilities involved in managing a data platform, including monitoring and managing releases, costs, and infrastructure changes.
  • Familiarity using AI tools to enhance the quality & pace of your output.

Technologies we love

  • Languages: Python, Spark, SQL
  • Tools: AWS, Azure, Git, Rest APIs, Kubernetes, Docker
  • Datastores: Databricks, OpenSearch, Postgres

Why it’s great to work at Altana

  • We love to collaborate, and we win as a team!
  • We are committed to engineering excellence
  • We value personal and professional development
  • We learn from diverse backgrounds and perspectives
  • We impact the world, from enabling developing countries to identifying drug traffickers

At Altana, we believe that a diverse workforce enables greater creativity, performance, and adaptability. We’re proud to be an equal opportunity employer and welcome you to join us as you are. Our employment opportunities and decisions are based on business needs and individual qualifications, without regard to race, color, religious creed, national origin, ancestry, age, physical or mental disability, medical condition, marital status, sexual orientation, gender identity or expression, genetic information, family care or medical leave status, military or veteran status, or any other characteristic protected by the laws or regulations in the areas in which we operate. We prohibit discrimination and harassment of any type, in any situation.

Offers related to employment at Altana will come from an Altana.ai email address. We will never ask for payment as part of the interview or onboarding process.

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.

How Many Machine Learning Tools Do You Need to Know to Get a Machine Learning Job?

Machine learning is one of the most exciting and rapidly growing areas of tech. But for job seekers it can also feel like a maze of tools, frameworks and platforms. One job advert wants TensorFlow and Keras. Another mentions PyTorch, scikit-learn and Spark. A third lists Mlflow, Docker, Kubernetes and more. With so many names out there, it’s easy to fall into the trap of thinking you must learn everything just to be competitive. Here’s the honest truth most machine learning hiring managers won’t say out loud: 👉 They don’t hire you because you know every tool. They hire you because you can solve real problems with the tools you know. Tools are important — no doubt — but context, judgement and outcomes matter far more. So how many machine learning tools do you actually need to know to get a job? For most job seekers, the real number is far smaller than you think — and more logically grouped. This guide breaks down exactly what employers expect, which tools are core, which are role-specific, and how to structure your learning for real career results.

What Hiring Managers Look for First in Machine Learning Job Applications (UK Guide)

Whether you’re applying for machine learning engineer, applied scientist, research scientist, ML Ops or data scientist roles, hiring managers scan applications quickly — often making decisions before they’ve read beyond the top third of your CV. In the competitive UK market, it’s not enough to list skills. You must send clear signals of relevance, delivery, impact, reasoning and readiness for production — and do it within the first few lines of your CV or portfolio. This guide walks you through exactly what hiring managers look for first in machine learning applications, how they evaluate CVs and portfolios, and what you can do to improve your chances of getting shortlisted at every stage — from your CV and LinkedIn profile to your cover letter and project portfolio.

MLOps Jobs in the UK: The Complete Career Guide for Machine Learning Professionals

Machine learning has moved from experimentation to production at scale. As a result, MLOps jobs have become some of the most in-demand and best-paid roles in the UK tech market. For job seekers with experience in machine learning, data science, software engineering or cloud infrastructure, MLOps represents a powerful career pivot or progression. This guide is designed to help you understand what MLOps roles involve, which skills employers are hiring for, how to transition into MLOps, salary expectations in the UK, and how to land your next role using specialist platforms like MachineLearningJobs.co.uk.