[Hiring] Data Engineer @World Food Programme

Role Description

The purpose of this assignment is to ensure the smooth flow of data from our fundraising platforms such as Meta, Google Search, Salesforce and others into our analytics warehouse. Once in the warehouse, data needs to be transformed and made reliably available for analytical, reporting and further marketing purposes and automations. The Senior Data Engineer plays a critical role in ensuring data-led decision making is the norm as we deliver the best supporter experience possible.

Key Responsibilities

• Continued development of our analytics warehouse, used by Individual Fundraising teams (Share The Meal and Individual Giving) for tactical and strategic decision making.
• Consolidate current and new data pipelines for the Extraction, Load and Transformation of data from a variety of in-house and third-party data sources.
• Ensure that the data pipelines have quality assurance checks to increase data reliability and improved latency.
• Assemble large, complex data sets that meet business requirements. Work with data analytics experts to strive for greater functionality in our data objects.
• Convert algorithms, models and features into production solutions within AWS and other components of the fundraising technical stack. Ensure these data models are available in marketing platforms such as Marketing Cloud, Braze or exported where required to third party platforms.
• Work with analysts and optimization specialists to automate key processes of routine tasks.
• Build and maintain a repository of scripts and codes, ensuring best practice version control using AzureOps.
• Set the standards for software engineering practices within the team. Help mentor existing data analysts on efficient coding, quality assurance and software control.
• Work with tech teams to expand and enhance the datasets in the BI warehouse.
• Management of data engineer direct reports.

Deliverables at the End of the Contract

• Development of a delivery roadmap. This will consist of a thorough review of existing data pipelines for efficiency and effectiveness, identification of new data sources and then a plan for prioritization.
• This plan needs to be managed and maintained as a data engineering workstream in Asana, allowing full visibility of projects, the functionality to add new tasks and to reprioritize to meet business objectives.
• A robust quality assurance system which can detect and then notify of any discrepancies existing across platform.
• Comprehensive code control, ensuring that business continuity is maintained and that the warehouse produces reliable and consistent data.
• Introduction of version control protocols and systems for the BI data analysts across their preferred platforms of Tableau and Python.

Qualifications

• At least six years’ progressive experience working in a data engineer or software development role.
• Six years’ experience of using Python (or similar scripting language), building data warehouses and building robust ETL processes.
• Experience of using AWS is essential and Tableau Server is desirable.
• Bachelor’s degree in engineering, computer science, physics, mathematics or similar. Master’s degree preferred.

Technical Expertise

• Up-to-date and thorough understanding of contemporary data engineering principles and practices, including tools, techniques, processes and methods, data modeling best practices and modern data architecture.
• Experience translating business requirements into iterative solutions and delivery of implementation.
• Excellent SQL knowledge and strong understanding of relational databases, best practices and optimization with AWS Redshift.
• Excellent Python development skills, preferably in performing transformation and analysis of datasets, implementation of statistical and machine learning models.
• Experience with custom data transformation, data formats and normalization, preferably with dbt, parquet, avro and RESTful APIs.
• Experience of implementation and orchestration of complex data pipelines using tools such as Airbyte, Airflow, Stitchdata or similar platforms.
• Experience applying software engineering best practices to data pipelines and analytics (version control, testing, automating data QA).
• Familiarity with marketing-based data models and CRM data is a plus (e.g. Meta Ads, Google Ads, BigQuery, Salesforce Marketing Cloud, Adjust, Braze).
• Familiarity with user behavior data models is a plus (e.g. Google Firebase Analytics / BigQuery, Amplitude, funnel analysis).

Soft Skills

• Familiarity with reverse ETL, making data actionable in CRM, Analytics and marketing automation tools.
• People-oriented. Uses tact and courtesy to give and receive information with a variety of individuals.
• Good attention to detail and strong communication skills.
• Ability to work to deadlines and follow clear instructions.
• Ability to think creatively and deliver on commitments.

Languages

• Excellent command of spoken and written English.
• Intermediate knowledge of another official UN language would be a plus.