Data Operations Analyst
OpenCorporates exists to make information about companies and the corporate world more accessible, more discoverable, and more usable, and thus give citizens, community groups, journalists, other companies, and society as a whole the ability to understand, monitor and regulate them. We're based in Hoxton, in the heart of London's technology hub.
OpenCorporates is the largest open database of companies and company data in the world, with in excess of 170 million companies from over 130 jurisdictions. Our primary goal is to make information on companies more usable and more widely available for public benefit, particularly to tackle the use of companies for criminal or anti-social purposes, for example corruption, money laundering and organised crime. Our customers include the likes of Mastercard, PwC, CapitalOne and Factset. By charging commercial users for proprietary access to the structured data, we can make our data available for free to journalists, NGOs and academics via our website and API. You can read more about the impact we have, and the data side of things, on our blog.
We are looking for a talented Data Operations Analyst to join our growing team and help us continue OpenCorporates’ important mission. We need proactive and positive team players with a drive to learn and to improve our tech and processes. You'll be interested in how to handle industrial quantities of complex data as we have over 200 data feeds to keep running smoothly, and under our newly appointed Chief Data Officer, we have started an ambitious mission to rapidly expand the breadth and depth of the data we collect.
What you'll be doing
- Overall you will ensure the smooth running of our data pipeline (our systems that fetch and ingest incoming data into OpenCorporates).
- You will monitor the data environments (e.g. through our dashboards and logs) to identify and escalate issues.
- You'll be diagnosing issues and resolving issues that occur, working as needed with other team members in our Data and Tech teams.
- Improving the way we work. You will be a key player in our goal to have a ruthless focus on efficiency and productivity improvements in order to maintain our competitive advantage, scale at pace, provide better and fresher data and minimise the human interaction
- Participating in the design of new processes and dashboards to efficiently manage our BAU tasks and allow us to see at a glance the current status of our 200+ data feeds.
- Working with the team to structure, systemise, automate and document our data pipeline to ensure our systems are scalable and reliable.
- Making sure that our internal stakeholders receive quality and timely status updates, issues are escalated promptly and queries are answered.
Relevant technical skills
One (or more) years of experience with data in a data operations analyst, data engineering or master data management roles. Above all we are looking for talented people who we think will fit in well, who are happy to be part of a team - sharing knowledge and learning from each other.
- Query and understand structured data within SQLite, MySQL and JSON
- Software development knowledge in Ruby or Python, Git, Linux shell scripting & tools
- ETL processes and data pipelines; data testing/quality assurance processes (script based languages as opposed to ETL tools)
- Data acquisition, analysis and quality management on large datasets
- Root cause analysis & data remediation experience
- Accuracy and attention to detail.
- Excellent verbal and written communication skills
Useful but not a prerequisite:
- Process improvement and automation
- Web scraping
- Competitive salary depending on experience.
- We offer 26 days holiday (plus public holidays).
- We will add you to our pension scheme.
- Are you interested in a conference, training course or book? You got it.
- If you want to work remotely sometimes because kids, Amazon deliveries, plumbers, sick cat etc., that's cool.
- We are an equal opportunity employer and value diversity at our company.
- We do not discriminate on the basis of race, religion, colour, national origin, gender, sexual orientation, age, marital status or disability status.