44 applicants

Company

Global Fishing Watch · 10 hours ago

Data Quality Analyst

United States

Full-time

Remote

Mid, Senior Level

$80K/yr - $90K/yr

5+ years exp

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Information Technology

No H1B

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Responsibilities

Conducting quality assurance checks and monitoring of evolving Big Data datasets, including AIS, VMS, SAR, VIIRS, and other types of vessel identification data from different sources.

Making visible to the organization and public the level of QA we have in the different datasets and owning the roadmap for adding QA to existing and new data.

Spreading a QA culture in the different areas of Global Fishing Watch through aiding in cross-team QA coordination and communication throughout each data pipeline.

Provide thorough reviews and assessments of methodology changes in data developed by the Research and Engineering teams at GFW, including different types of data such as AIS, VMS, SAR, VIIRS, etc.

Work collaboratively across teams and specifically with Engineering to develop automated and continual quality control checks on productive pipelines’ outputs to detect anomalies immediately and ensure that the data published in APIs is consistent with the pipeline outputs.

Understand and act as a knowledge source of GFW data sources and pipelines, from ingestion of data to published data products in APIs.

Manage JIRA task management of QA tasks.

Aid in transitioning public facing data pipelines from an early ‘prototype’ stage to ‘production’ by improving release processes, pipeline consistency and stability, as well as promoting quality assurance best practices across various teams.

Work with other team members, create, organize, and track metrics to communicate quality assurance improvements and changes both for internal and external audiences.

Highlight the improvements and progress in quality assurance at GFW internal and external audiences through the creation of public dashboards and performance metrics.

Aid in standardizing metadata requirements and data documentation.

Work closely with the other Data Team members to institutionalize Global Fishing Watch standard QA protocols across all projects and teams.

Along with the Data Team and Engineering Team continue to advance understanding and cohesive use of the data staging concepts and requirements of datasets to move from proof-of-concept to published.

Aid in the standardization and improvement of QA tools used for pipeline review, including review templates for change impact assessment, automated monitoring alerts, and anomaly detection.

Develop and maintain an informed awareness of relevant topics to continually innovate on the application of GFW products to aid in the the sustainability of our ocean.

Assist other team members with any ongoing needs, such as review of user reported data errors, data communication with external partners, and answering questions regarding data and our methodologies from external partners and internal teams.

Qualification

Find out how your skills align with this job's requirements. If anything seems off, you can easily click on the tags to select or unselect skills to reflect your actual expertise.

Data QA experienceSQLPythonData visualizationBig Data datasetsAPIsQA/QC processesAgile methodologiesRPower BILookerGgplot2ShinyMatplotlibPlotlyData ethicsData accessibility standardsFisheries complianceFisheries monitoringGoogle BigQueryAISVIIRSSARVMSMetadata documentationAnomaly DetectionChange impact analysisData unit test developmentFluent SpanishIntellectually curious

Required

Master's degree in a relevant area or equivalent professional experience (such as Bachelor’s degree with 5+ years of experience in quality assurance, software engineering, data analytics, and/or fisheries science)

Demonstrated track record of attention to detail, for example catching issues while reviewing pull requests or conducting root cause analysis of issues

Demonstrated skills in QA/QC processes, specifically the ability to develop and carry out testing methodology to quantify change, inaccuracies, and inconsistencies in the data

Trained in presenting QA findings and metrics in a digestible format to various audiences with the corresponding level of detail.

Fluency with SQL and another coding language, such as Python or R

Proficiency in data visualization either through BI tools such as Power BI or Looker, or through packages such as ggplot2, Shiny, matplotlib, or plotly

Experience with QA of public facing data products

Demonstrated knowledge of best practices in evolving data and data quality

Knowledge of agile methodologies to work on sprints and participate in planning meetings

Fluent English speaker

Good judgment and the ability to make and justify recommendations

Excellent written and oral communication skills in English to effectively collaborate with designers, developers, product managers, and other relevant staff members or clients, and communicate complex technical and scientific information to non-technical audiences

Team player, willing to work with, teach and learn from the GFW team

Comfortable working in a small but fast-growing organization, with changing instructions and requirements

Intellectually curious, forward-thinking, willing to suggest/try new technologies and creative approaches to problems

Ability to manage multiple projects and meet deadlines

Demonstrated ability to work remotely and asynchronously

Preferred

Skilled data communicator and educator, trained in data ethics and accessibility standards

Knowledge of big data pipelines and APIs

Experience in fisheries compliance and/or monitoring, control and surveillance, especially regarding fisheries supply chain

Fluency in Google BigQuery

Knowledge of AIS, Visible Infrared Imaging Radiometer Suite (VIIRS), synthetic aperture radar (SAR), VMS and other satellite data

Experience with metadata documentation and maintenance for Big Data

Strong analytical skills, specifically understanding how to detect and replicate data errors and inconsistencies, how to detect changes in time series and evolving datasets, and how to develop reports to effectively communicate changes to team members. Specifically, this involves experience in Anomaly Detection, analysing differences in datasets across environments or versions, data unit test development, change impact analysis, and other change detection and data monitoring methodologies

Fluency in Spanish