RAKBANKSenior Data Engineer
RAKBANK is hiring a Senior Data Engineer. Level rates it ; you can apply on Level.
AI in this role
Lead the enterprise data platform engineering, Databricks lakehouse operations, and data pipelines supporting analytics and AI initiatives.
Rakbank is seeking an experienced Lead Data Engineering / Platform Operations professional to lead the engineering, operations, reliability, and continuous evolution of the Bank's enterprise data platform. This role will be responsible for building and operating scalable data pipelines, managing the Databricks Lakehouse platform, driving DataOps best practices, and enabling analytics, AI, regulatory reporting, and operational intelligence across the Bank. Working closely with Enterprise Architecture, Data Modelling, AI Engineering, and Infrastructure teams, you will ensure the platform remains secure, governed, reliable, and cost-efficient.
What You Will Do
- Lead the design, development, and operation of enterprise-scale data ingestion pipelines across batch, micro-batch, and real-time streaming environments.
- Engineer and manage RAKBANK's Databricks Lakehouse platform, including Delta Lake optimisation, performance tuning, and platform reliability.
- Implement and govern Unity Catalog, including data security controls, lineage tracking, access management, and compliance requirements.
- Build and maintain dbt transformation frameworks, testing standards, documentation, and CI/CD integration.
- Drive DataOps excellence through automated testing, monitoring, observability, incident management, and platform support processes.
- Manage Confluent/Kafka streaming and CDC capabilities, ensuring resilient and scalable real-time data movement.
- Partner with AI Platform Engineering teams to support feature pipelines, vector data services, and AI-powered data products.
- Own platform FinOps activities, optimizing cloud spend across Databricks, Azure Data Factory, Confluent, and storage services.
- Ensure compliance with data security, privacy, governance, and regulatory requirements.
- Lead, coach, and develop a high-performing team of Data Engineers while establishing engineering best practices and standards.
What We Are Looking For:
- 10+ years of experience in Data Engineering, including at least 3 years in a technical leadership capacity.
- Strong hands-on expertise with Databricks, including Delta Lake, Unity Catalog, Databricks Workflows, PySpark, and Spark SQL.
- Proven experience with Azure Data Factory (ADF) for enterprise data integration and orchestration.
- Deep experience with Confluent/Kafka, CDC technologies, schema management, and event-driven architectures.
- Strong knowledge of dbt, automated testing frameworks, DataOps practices, and CI/CD pipelines.
- Experience managing platform reliability, data quality, observability, and incident response.
- Understanding of cloud cost optimisation, FinOps, and platform governance.
- Ability to collaborate effectively with Data Architects and Data Modelers while translating architecture into scalable engineering solutions.
- Bachelor's degree in Computer Science, Data Engineering, Information Technology, or a related discipline.
- Databricks Certified Data Engineer Professional and/or Azure Data Engineer certifications are highly desirable.
How we rate this
Senior Data Engineer at RAKBANK rates 65 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.
Works on AI. The daily work is on AI products, without building the model.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.
Prepare for this job
A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.
Skills and AI tools this role asks for
Questions you could be asked
- Tell me about a project where data engineering was part of your work. What did you do?
- Tell me about a project where dataops was part of your work. What did you do?
- Tell me about a project where lakehouse was part of your work. What did you do?
- Tell me about a project where etl was part of your work. What did you do?
- Tell me about a project where pipeline orchestration was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: Data Engineering, Dataops, Lakehouse, ETL, and Pipeline Orchestration. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
- Show where AI is part of your daily process, not a one-off project — this role expects it to be a running habit.
Want an expert to read your CV for this job?
Free. Send your CV and the role you want next. We reply by email within 2 to 4 business days.
Get new data engineer jobs (Works on AI ●●●○ or higher) by email
One email a week with the new data engineer jobs (Works on AI ●●●○ or higher), each rated for how much AI is in the work. No recruiter spam, unsubscribe in one click.
Free. One email a week. Unsubscribe in one click.
Similar roles
Data roles that work on AI, at other companies.
What kind of AI work fits you?
Answer 12 practical questions in about three minutes. Get a simple profile, the work it points to, and live roles to explore next.
Find my next step