Senior Data Engineer MMH

Role Purpose

The Senior Data Engineer is responsible for delivering and evolving data engineering capabilities that enable trusted analytics, reporting, and insight generation across Momentum Investments. The role focuses on the design, build, and operational support of scalable data pipelines and data platforms, ensuring data is secure, high-quality, and readily available to downstream consumers. Operating within an Agile delivery environment, the Senior Data Engineer works closely with fellow Data Engineers, analytics and BI teams, Product Owners, and business stakeholders.

Beyond hands-on engineering, this role carries accountability for technical direction within the team, supporting design decisions, uplifting engineering standards, and guiding the use of AI capabilities in a controlled, governance-aligned manner to improve delivery effectiveness.

• Bachelor’s degree in Computer Science, Information Systems, Engineering, or a related discipline. Relevant certifications are beneficial.
• 4–7+ years of professional experience in data engineering or related roles.
• Demonstrated experience delivering production-ready data pipelines and platforms.
• Strong exposure to AWS-based data architectures.
• Hands-on experience working within Agile or SAFe delivery environments.
• Exposure to implementing AI tooling or capabilities within engineering workflows.
• Demonstrated ability to apply AI responsibly in engineering work, including validation of outputs.
• Practical experience using AI to support data pipeline understanding, optimisation, testing, or documentation.
• Advanced Python and SQL capabilities.
• Strong foundation in data modelling, analytics-oriented schema design, and data warehousing principles.
• Experience ingesting data from relational databases, cloud storage, APIs, and file-based sources.
• Proficiency with Git-based version control, CI/CD pipelines, and automation.
• Familiarity with analytics and BI tools such as Power BI.

• Contribute to the delivery of data engineering outcomes aligned to sprint goals and program-level commitments.
• Actively engage in Agile ceremonies, contributing to planning, estimation, prioritisation, and continuous improvement discussions.
• Decompose data features into implementable tasks and provide reliable effort estimates.
• Ensure outputs meet agreed functional, performance, and data quality expectations.

• Design and implement data ingestion and transformation pipelines across multiple systems and data domains.
• Build solutions that support scalable batch and incremental processing patterns.
• Ensure robustness of pipelines through appropriate error handling, monitoring, and alerting.
• Implement data validation and reconciliation mechanisms to maintain confidence in data assets.

• Design data solutions that align with Momentum Investments’ data platform strategy and target architecture.
• Contribute to the ongoing evolution of the cloud-based data environment (AWS-aligned).
• Assess the impact of design choices on security, performance, cost, and supportability.
• Identify integration points, upstream/downstream dependencies, and potential risks early in the delivery lifecycle.

• Provide guidance and technical oversight to less experienced data engineers.
• Support analytics, BI, and data science teams with clarity on data structures, availability, and pipeline behaviour.
• Encourage sound engineering judgment, curiosity, and continuous learning within the team.
• Actively contribute to defining shared standards, patterns, and best practices.

• Review data engineering code and configuration to uphold consistency, reliability, and maintainability.
• Drive improvements through optimisation and simplification of existing pipelines and data models.
• Apply disciplined engineering practices including version control, automated testing, CI/CD, and structured releases.
• Ensure solutions are documented sufficiently for operational support and future changes.

• Promote responsible use of AI to enhance…