Data Ops Engineer

Collinson

Collinson is a global loyalty and benefits company.

We use our expertise and products to craft customer experiences which enable some of the world's best known brands to acquire, engage and retain the most demanding and choice-rich customers. In particular, our unique expertise and insight into high earning, frequent travellers allows us to create products and solutions for our clients that inspire greater customer engagement to drive more profitable relationships, enrich their travel experiences, protect what matters and assist in in times of need.

While specialising in Financial Services, Travel and Retail, we also support clients in multiple sectors. We have worked with over 90 airlines, 20 hotel groups and more than 600 financial institutions and banks, with clients including Accor Hotels, Air France KLM, American Express, British Airways, Cathay Pacific, Diners Club, Mandarin Oriental, Mastercard, Radisson Hotel Group, Sephora, Visa and Vhi.

We take our 30 years' experience working with these kinds of household names in over 170 countries, and help our clients to deliver the smarter experiences it takes to differentiate their propositions, and help them win deeper devotion with their customers.

Collinson is a privately-owned entrepreneurial business with 2,000 passionate people working in 20 locations worldwide. Our solutions include Priority Pass, the world's best known airport experiences programme, while we are also the trusted partner behind many of the leading financial services, airline and hotel brand's reward programmes and loyalty initiatives.

Purpose of the job

We are seeking a highly skilled DataOps Engineer to join our growing platform team. The successful candidate will play a critical role in delivering innovative and customer-centric data solutions, with a focus on hands-on execution and quick delivery of reports and insights.

We are in an exciting period of evolution and looking for a DevOps Engineer to support the build of our new Data Platform which comprises Data Lakes in AWS and Data Warehouses in Snowflake.

As a Data DevOps Engineer you will productionise data pipelines as well as data & analytics solutions. You will evangelise and continuously improve Collinson DevOps capabilities as well as ensuring that all Data products and projects are designed, delivered and supported according to business requirements.

Key Responsibilities

• Productionize and maintain data pipelines to ensure data quality and operationalization.
• Be at the centre of the build of the company's new data platform, which includes Data Lakes in AWS and Data Warehouses with cutting-edge tools and technology.
• Evangelize and continuously improve the company's DataOps capabilities.
• Ensure that all data products and projects are designed, delivered, and supported according to business requirements.
• Collaborate with cross-functional teams to understand and interpret business requirements and translate them into technical solutions.
• Implement and maintain processes for data quality, data validation, and data governance.
• Monitor and maintain the performance and reliability of data pipelines and data systems.
• Investigate and troubleshoot data issues and implement solutions to resolve them.
• Continuously improve the data operations processes and tools to ensure scalability and efficiency.
• Act as a subject matter expert and provide guidance to other teams on best practices for data operations.

Day to Day Activities will include

• Monitoring and maintaining data quality: This includes performing regular checks on the data pipelines and ensuring that all data is accurate, consistent and meets the required standards.
• Automating data operations: Implementing automation tools and processes to streamline data operations, reduce manual errors, and improve efficiency.
• Managing data security and privacy: Ensuring that all data is securely stored and processed, and that proper security and privacy measures are in place to protect sensitive data.
• Managing data storage and retrieval: Designing and implementing data storage solutions that are scalable, efficient, and optimized for quick retrieval.
• Optimizing data pipeline performance: Constantly monitoring and optimizing data pipeline performance to ensure that data is delivered to stakeholders in a timely and accurate manner.
• Collaborating with cross-functional teams: Working closely with stakeholders, such as data analysts and data scientists, to understand their data needs and to help them get the data they need to support their work.
• Staying current with new technologies: Continuously researching and staying current with new data technologies and trends, and recommending new tools and processes to improve data operations.
• Ensuring data compliance: Ensuring that all data operations comply with industry regulations, such as GDPR and HIPAA.

Knowledge, skills and experience required

Knowledge

• Experience with AWS cloud services and Data Lakes, Snowflake, and other data warehousing technologies
• In-depth understanding of data pipeline architecture and data modelling practices
• Understanding of data governance and data security practices
• Knowledge of data-driven analytical and reporting activities
• Understanding of the impact of changes to business rules on data processes
• Strong knowledge of SQL and scripting languages (e.g. Python, Bash)
• Experience with Infrastructure as Code, including a working knowledge of Terraform
• Familiarity with CI/CD driven data pipeline and infrastructure

Skills

• Hands-on experience deploying, maintaining and monitoring data pipelines.
• Excellent problem-solving skills and ability to provide clear recommendations
• Innovative thinking and the ability to continuously improve data processes
• Strong communication and influencing skills, especially in regard to data solutions and outcomes
• Ability to manage and lead a small team of data engineers

Experience

• Extensive experience leading cloud data platform transformations, particularly in AWS
• Proven track record of delivering large-scale data and analytical solutions in a cloud environment
• Experience in developing Data Warehouses
• Experience in cost-effective management of data pipelines
• Experience with Agile delivery approach using Scrum and Kanban methodologies
• Experience in supporting QA and user acceptance testing processes