Senior Data Developer

At U.S. Bank, we’re on a journey to do our best. Helping the customers and businesses we serve to make better and smarter financial decisions, enabling the communities we support to grow and succeed in the right ways, all more confidently and more often—that’s what we call the courage to thrive.   We believe it takes all of us to bring our shared ambition to life, and each person is unique in their potential. A career with U.S. Bank gives you a wide, ever-growing range of opportunities to discover what makes you thrive. Try new things, learn new skills and discover what you excel at—all from Day One.

As a wholly owned subsidiary of U.S. Bank, Elavon is committed to building the platforms and ecosystems that help over 1.5 million customers around the world to achieve their financial goals—no matter what they need. From transaction processing to customer service, to driving innovation and launching new products, we’re building a range of tailored payment solutions powered by the latest technology. As part of our team, you can explore what motivates and energizes your career goals: partnering with our customers, our communities, and each other.

We actively uphold transparent and fair hiring practices that support individual opportunity, inclusive culture, and career mobility across all levels of our organisation.

We offer meaningful opportunities for growth, a culture of inclusion, and a strong commitment to transparency and integrity in everything we do.

Job Description

The Senior Data Developer is responsible for designing, building, and enhancing data products that enable trusted, high‑quality, and decision‑ready data across the organisation. This role will lead hands‑on development across data pipelines, data quality controls, metadata management, and lineage, ensuring that data assets are discoverable, governed, and fit for purpose.

A core part of the role is partnering with Data Governance and business stakeholders to operationalise governance within delivery—leveraging Collibra to define and maintain metadata, policies, ownership, quality rules, and lineage—while delivering scalable data platforms and dashboards that improve how teams make and measure decisions.

1. Accountabilities and Responsibilities

Data Platform & Pipeline Development

• Design, develop, and optimise scalable data pipelines (batch and/or streaming) to ingest, transform, and curate data from multiple internal and external sources.

• Build and maintain curated datasets and semantic layers that support analytics, reporting, and operational use cases.

• Apply best practices in modular design, automated testing, CI/CD, monitoring, and operational support.

• Ensure solutions meet performance, resiliency, and security requirements appropriate to the organisation’s operating model.

Data Quality Engineering & Management

• Define, implement, and manage data quality frameworks and controls (e.g., validation rules, completeness, accuracy, timeliness, uniqueness, and integrity).

• Develop automated data quality checks and dashboards, including thresholds, alerts, and trend reporting.

• Partner with Data Owners and Stewards to triage, remediate, and prevent recurring data quality issues via root‑cause analysis.

• Embed data quality gates into pipelines and release processes, enabling measurable improvements in data trustworthiness.

Metadata, Lineage & Governance Enablement (Collibra)

• Configure and maintain metadata assets within Collibra, including business glossary terms, technical metadata, ownership, classifications, policies, and data quality rules.

• Establish and maintain end‑to‑end data lineage across platforms and products, ensuring transparency from source to consumption.

• Collaborate with Data Governance to align development practices with standards for metadata, data cataloguing, access controls, and retention.

• Support audits and governance reporting by ensuring documentation and metadata are complete, accurate, and consistently maintained.

Analytics & Decision Enablement (Dashboards / Data Products)

• Build data products that support decision‑making, such as operational dashboards, management reporting datasets, and self‑service analytics assets.

• Partner with stakeholders to translate business questions into measurable metrics, ensuring consistent definitions and governed KPI logic.

• Improve usability and adoption of analytics outputs by enabling discoverability through cataloguing and clear documentation.

• Support controlled access to data products, ensuring compliance wi