Senior Implementations Data Engineer

Altana
Charing Cross, United Kingdom
2 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Senior
Compensation
£ 54K

Job location

Charing Cross, United Kingdom

Tech stack

Artificial Intelligence
Amazon Web Services (AWS)
Azure
Network Analysis
Customer Data Management
Information Engineering
Data Governance
Data Security
Data Systems
Python
PostgreSQL
Machine Learning
Software Engineering
SQL Databases
Data Ingestion
Spark
GIT
Kubernetes
REST
Data Pipelines
Docker
Databricks

Job description

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, * Languages: Python, Spark, SQL

  • Tools: AWS, Azure, Git, Rest APIs, Kubernetes, Docker

  • Datastores: Databricks, OpenSearch, Postgres

  • 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

Requirements

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.

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