Analytics Engineer
Role details
Job location
Tech stack
Job description
We are looking for a skilled Analytics Engineer to join our team and help build and maintain robust data pipelines that support our analytics applications. The Data Engineering team has recently undergone a technology transformation to migrate from our legacy data warehouse to a brand-new data platform (Snowflake + dbt
- Argo Workflows + Kafka) to better enable the exciting needs of our data stakeholders (Data Science, Machine Learning and Business Intelligence, etc.). Having built a strong technology foundation, we are now looking for ways to improve the value that we deliver to our data stakeholders. The ideal candidate will have a strong background in data engineering, analytics and be proficient in designing, building, and deploying scalable data pipelines. Product analytics is the practice of using data to inform decision-making related to user behaviour, product development and improvement. As an Analytics Engineer, you will work closely with the Data Science, Product teams and Business teams to build data pipelines and analytical products to support self-serve analytics, data-driven experimentation in Product Engineering. Diversity and inclusion are a priority for us and we are making sure we have lots of support for all of our people to grow at giffgaff. Data and software engineering is at the heart of what we do here at giffgaff - our agile engineering teams build and support a set of applications and services that combined create our unique user experience on the giffgaff website, enable our internal teams to work in the most productive and efficient ways and enable a whole range of awesome features via modern APIs, events and microservices.
We have a culture of building and owning all the code that we use, and take pride in this. This allows us to keep full control on what's going on and how we shape solutions., * Design and implement robust data models (e.g., star schema, snowflake schema, data vault).
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Develop and maintain dimensional data models to support BI and reporting requirements.
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Develop and implement analytics solutions to track key performance metrics
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Design and build data pipelines to collect, process, and store large volumes of structured and unstructured data from various sources.
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Develop and maintain data quality checks and data validation processes.
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Develop and automate reports, dashboards, and data visualisations to communicate insights and trends effectively to stakeholders.
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Build and maintain tooling and frameworks to automate data pipelines for experimentation and ML modelling
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Develop and maintain a deep understanding of product domains to ensure relevant events are produced and new entities and processes are integrated downstream in the Snowflake data platform model
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Monitor and troubleshoot data pipeline issues and provide timely resolution.
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Work closely with product managers, data scientists, product analysts and software engineers to identify analytical requirements.
Requirements
Must have:
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Bachelor's degree in computer science, engineering, mathematics, or a related field.
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3+ years of experience in data/analytics engineering with a focus on building data pipelines.
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Proficiency in SQL and experience with one or more programming languages such as Python, Java.
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Experience with modern cloud data warehouse platforms such as Snowflake, BigQuery, Redshift or similar.
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Experience with cloud-based data platforms, particularly AWS or GCP.
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Experience with data warehousing, data modelling, and ETL development.
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Strong analytical & communication skills and an understanding of what drives the performance of a product to reach the company's commercial goals.
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Hands-on experience with data visualisation tools such as Tableau, Looker, Streamlit or Power BI.
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Strong problem-solving skills and attention to detail. Valuable skills:
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Previous experience in similar analytics engineering roles with focus on product analytics and data modelling is highly desirable.
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Experience working with distributed event stores and stream-processing platforms such as Kafka of Kinesis.
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Experience working with batch processing frameworks, such as DBT, Argo Workflows, Apache Airflow, etc.
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Familiarity with Docker, Kubernetes, Amazon EKS
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Familiarity with Continuous Integration with GitHub Actions
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Familiarity with Test-Driven Development and XP
Benefits & conditions
work, define our culture and we encourage everyone to bring their whole selves to the gaff. That's why we believe in creating an equitable, fairer, more inclusive business that champions different ideas and perspectives. We may be sort-of-small but we're big on that caring, sharing thing & strive to create a supportive culture. As a lean organisation, our team is built of a diverse, spirited range of people who are multi-skilled, highly motivated and flexible. In return for your outstanding efforts, you'll be rewarded with a competitive salary and excellent benefits. We believe that hard work should be supported and recognised.