Data Engineer

Who is HelloKindred?

HelloKindred are specialists in staffing marketing, creative and technology roles, offering a range of talent solutions that can be delivered on-site, remotely or hybrid.

Our vision is to make work accessible and people’s lives better. We do this by disrupting traditional employment barriers – connecting ambitious talent to flexible opportunities with trusted brands.

Anticipated Contract End Date/Length: December 31, 2026
Work set up: Hybrid (2–3 days per week in office)
Clearance required: BPSS checks. Candidates must be eligible for BPSS clearance

Our client in the Information Technology and Services industry is looking for a Data Engineer with strong Spark, Scala, and Python skills to develop, maintain, and troubleshoot data orchestration workflows and reusable engineering components. The role will support the processing, transformation, validation, and delivery of large-scale financial datasets, while contributing to platform engineering, production support, monitoring, automation, and operational resilience. The successful candidate will work across application, platform, database, infrastructure, and downstream teams to maintain reliable data processes and ensure compliance with technology, security, and change standards.

Responsibilities

• Develop, maintain, and troubleshoot data orchestration workflows using Apache Airflow for extract generation, data publishing, feed delivery, and operational batch processes.
• Build and support reusable engineering components using Python, Scala, and Sharedview Spark to process, transform, and validate large-scale financial datasets.
• Design, write, and optimize SQL/PostgreSQL and Starburst/Trino queries for metadata processing, data validation, reconciliation, and operational investigation.
• Support Output Gateway production issues, including failed DAGs, delayed extracts, missing files, data mismatches, checksum failures, logs, status updates, and downstream delivery exceptions.
• Contribute to platform engineering and release activities using GitLab, Docker, and controlled CI/CD practices across DEV, UAT, and production-like environments.
• Enhance monitoring, logging, alerting, audit tracking, and automation to improve operational stability, supportability, and evidence for control processes.
• Work with application, platform, database, infrastructure, and downstream teams to diagnose issues end-to-end and implement safe, controlled fixes.
• Maintain a strong risk and control mindset by ensuring changes are tested, reviewed, documented, and released in accordance with technology, security, and change standards.

• Strong skills and experience in data engineering using Spark, Scala, and Python.
• Experience developing, maintaining, and troubleshooting Apache Airflow workflows for data orchestration and operational batch processes.
• Hands-on experience building reusable engineering components to process, transform, and validate large-scale financial datasets.
• Proficiency in SQL and PostgreSQL, including query design, optimization, metadata processing, data validation, and reconciliation.
• Experience supporting production data workflows and troubleshooting failed DAGs, delayed extracts, missing files, data mismatches, checksum failures, and downstream delivery exceptions.
• Familiarity with GitLab, Docker, and controlled CI/CD practices across development, UAT, and production-like environments.
• Understanding of monitoring, logging, alerting, audit tracking, and automation to improve operational stability and supportability.
• Ability to collaborate with application, platform, database, infrastructure, and downstream teams to diagnose and resolve technical issues.
• Strong awareness of risk, controls, testing, documentation, and technology, security, and change standards.

Desirable Skills / Preferred Qualifications

• Experience with Starburst/Trino, AWS S3 concepts, and distributed query behavior for large-dataset validation and troubleshooting.
• Exposure to React JS or API-driven operational user interfaces for configuration, monitoring, and support workflows.
• Familiarity with OpenShift, Kubernetes, Helm, or container platform deployments in enterprise environments.
• Understanding of financial data controls, auditability, reconciliation, data lineage, operational resilience, and data quality expectations.

All your information will be kept confidential according to EEO guidelines.

Candidates must be legally authorized to live and work in the country where the position is based, without requiring employer sponsorship.

HelloKindred is committed to fair, transparent, and inclusive hiring practices. We assess candidates based on skills, experience, and role-related requirements.

We appreciate your interest in this opportunity. While we review every application carefully, only candidates selected for an interview will be contacted.

HelloKindred is an equal opportunity employer. We welcome applicants of all backgrounds and do not discriminate on the basis of race, colour, religion, sex, gender identity or expression, sexual orientation, age, national origin, disability, veteran status, or any other protected characteristic under applicable law.