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: May 7, 2027

Work set up: Hybrid (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 / Analytics Engineer to play a critical role in building and maintaining the monitoring, controls, and observability capabilities for the HSBC Productivity Suite. This role will focus on designing and implementing robust ETL/ELT pipelines, developing data models for management information (MI) reporting, and creating dashboards that provide actionable insights for operational, risk, and compliance stakeholders.

• Design, build, and maintain scalable ETL/ELT pipelines to ingest and process log and event data from AI platform components.
• Develop and optimize data models for aggregation, reporting, and analytics to support MI and governance requirements.
• Collaborate with platform, DevOps, and security teams to ensure comprehensive data capture for monitoring and controls.
• Create and maintain dashboards and visualizations using tools such as Power BI, Tableau, Kibana, or Grafana.
• Write efficient SQL, Python, or Spark code for data extraction, transformation, and analysis.
• Implement data quality checks and validation processes to ensure the accuracy and reliability of monitoring data.
• Support automated alerting and reporting for operational incidents, policy violations, and compliance metrics.
• Document data flows, models, and dashboard logic to ensure transparency and auditability.
• Participate in requirements gathering with business, risk, and compliance teams to ensure MI meets governance standards.
• Continuously improve data pipelines and analytics solutions for performance, scalability, and usability.

• 5+ years of experience in data engineering, analytics engineering, or a related field.
• Strong experience designing and implementing ETL/ELT pipelines for large-scale log or event data.
• Proficiency in data modeling, aggregation, and building MI and reporting solutions.
• Hands-on experience with dashboarding and visualization tools such as Power BI, Tableau, Kibana, Grafana, or similar.
• Advanced SQL skills and experience using Python or Spark for data processing and analytics.
• Familiarity with cloud data platforms, including Azure, AWS, or GCP, and modern data architectures.
• Experience working with monitoring, observability, or security log data is a strong plus.
• Understanding of data governance, privacy, and compliance requirements in enterprise environments.
• Excellent problem-solving, communication, and documentation skills.
• Ability to work collaboratively in a cross-functional, agile team environment.
• Experience in regulated industries, such as banking, insurance, or healthcare.
• Knowledge of AI/ML platform monitoring and controls.
• Experience with log aggregation tools, such as ELK Stack or Splunk.
• Familiarity with operational risk, compliance, or audit reporting.

Additional Information

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.