Analytics Engineer

Job Purpose

The Intermediate Analytics Engineer is a rising data professional who will begin their careers as part of the analytics engineering team to create strong, interconnected, and effective data products that provide first-rate, use-case led analytics across the organization. The role involves collaborating with senior or leading analytics engineers to construct data products and pipelines for high-impact projects that offer scalability and automation, and improve data availability and quality. The Intermediate Analytics Engineer has a zeal for honing their competencies in data-, cloud-, and software engineering to deliver analytic use-cases that generate business value and drive data as a competitive edge.

Role Description

• Formulate and sustain data pipelines using SQL and Python to produce reliable, scalable, and fit-for-purpose data products in a cloud environment.
• Convert technical requirements into reliable, scalable data products or pipelines that cater to the organization's requirements.
• Cooperate with data scientists and analysts to comprehend data needs and furnish data products for analytics use-cases.
• Execute monitoring, testing, and automation practices for data products.
• Engage in code reviews, ensuring observance of coding standards and best practices.
• Collaborate with team members to identify and resolve data-related problems and propose solutions.
• Provide primary support for data pipelines.
• Contribute to the formulation and maintenance of documentation for datasets and analytical processes, ensuring that consistent terminology and definitions are used to facilitate seamless teamwork.
• Contribute to the creation of a library of reusable software engineering artifacts aimed at accelerating the creation of data products.
• Preserve technical documentation related to data products and pipelines.
• Streamline and implement components within a data product.
• Support DataOps initiatives within the team.
• Jointly work with the team to carry out standard testing procedures and conduct regular monitoring of datasets, with a focus on data accuracy and quality as a significant contributor to our analytics schemes.
• Participate in the incorporation and adoption of software engineering best practices within the data team, contributing to the enforcement of coding standards, version control, and cooperative workflows.

Experience and Skills

• A Degree or Diploma in Computer Science, Software Development, Engineering, or a related field.
• A minimum of 1 year of hands-on experience in a data team, functioning as a data engineer or data-centric software engineer.
• A knowledge of modern data processing tools and technologies, contributing to the development, refinement, and productionization of data products.
• Expertise in Python and SQL, capable of undertaking development tasks.
• Familiarity with the basic concepts of using Apache Spark for distributed computing, acquired through coursework or initial projects.
• Familiarity with cloud platforms such as AWS, Azure, or Google Cloud through coursework or basic projects, with a basic understanding of cloud concepts related to computation and storage.
• Basics of Infrastructure as Code and its importance in data engineering processes.
• Possessing an exposure to handling voluminous data sets and understanding business models.
• Basic understanding of software development best practices and version control systems (e.g., Git).
• A commitment to coding standards, encompassing code readability, effective commenting, and consistent naming conventions.
• Understanding of core testing methodologies to ensure code quality.
• Willingness to learn and adopt established coding patterns and best practices within the team.
• Experience of collaboration within and across multifunctional teams.
• Experience of working within an Agile environment.