Data Lead for Global Public Health at Field (Berlin, Germany) (allows remote)

We’re looking for a (normal-to-big) data engineer to help us build and maintain our suite of country-scale logistics and program intelligence systems for distributed, occasionally-connected contexts. Our ideal data engineer will be an experienced cross-functional collaborator and able to contribute to:

Data analysis environments - At Field, data drives all aspects of business, and your role will be to design and build the tools to ensure data science, management and engineering all have the tools and services they need to consume and manage it.

Data infrastructure - Working with our engineering team, your job will include driving database optimisation and data architectures to expand our data warehousing, analysis and pipeline architecture.

Data driven products - As part of a multi-disciplinary team you will help investigate internal data consumers' needs and design solutions to provide flexible, transparent, reliable tools and environments for data management and analysis.

Data analysis - Diving into our trove of near-realtime data, and perform robust investigative analyses to drive business results in fields such as supply planning, demand planning and anomaly detection.

You will work closely with other engineers and product teams in Berlin and Nigeria, supporting each other and collaborating through frequent architecture and code reviews and strong adherence to best practices, as we develop tools to shape health supply chains at scale in some of the fastest growing places in the world.

Responsibilities

• Assemble large, complex data sets as needed by business and operational consumers


• Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing database schema and infrastructure for greater scalability, etc


• Build the infrastructure required for querying, transformation and analysis of data from a range of sources including SQL databases, noSQL databases, REST APIs, and file formats


• Design and implement data QA plans and automated tooling with engineering


• Build analytics tools that utilize the data pipeline to provide actionable insights into supply chain operations, operational efficiency and other key business performance metrics


• Architect and implement measures to ensure data integrity and security across all backend infrastructure


• Research and iterate on advanced statistical and ML-augmented data tools to improve planning and operations

Required

• Advanced working knowledge of and professional experience with querying and manipulating data using relational databases (postgres), document databases (elasticsearch, couchdb), spreadsheets (google sheets, excel) and REST APIs


• Pro SQL and relational database management skills


• Professional experience applying advanced statistical methods to data management and analysis


• Experience performing root cause analysis on internal and external data and processes to answer specific business questions, and identify discrepancies and opportunities for improvement


• Strong analytic skills related to working with unstructured datasets


• Professional experience configuring and maintaining analytical tools including business intelligence suites (preferably open source) and GIS platforms for analysis and routing


• Working knowledge of message queuing, stream processing, and serverless infrastructure


• Excellent technical communication skills and proven ability to problem solve with a multi-disciplinary team


• 6+ years of experience in a database management, data science role or equivalent


• Graduate degree in Computer Science, Statistics, Informatics, Information Systems or another mathematical or scientific field


• Professional experience in demand forecasting and supply planning


• Location: Berlin

Bonus

• Experience with ERPs/enterprise management systems


• Desire to travel to work with our international teams


• Strong gif game

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