We are looking for an experienced data developer to support
a new analytics platform in production and contribute to its upcoming release
within a large financial services organization. The solution integrates data
from multiple systems in an Azure cloud environment and makes it available
through a data warehouse using Power BI. The project is progressing in
iterations, each delivering value to users, until the planned handover to the
operations team in summer 2027. You will be central to the stability and
evolution of the solution: providing technical support after production
releases, monitoring the platform, resolving issues with the team, developing
ETL processes, and configuring data ingestion pipelines from source systems to
data lakes. You will participate in data valuation and the configuration of the
data warehouse according to the established model, perform unit testing, and
document the processes.

The client
is seeking a data developer with 8+ years of experience to initially provide
production support for the Group Insurance Data Hub, while continuing to
contribute to Release 2. The core of the role is data engineering on the Azure
stack: data ingestion into data lakes, dimensional modeling (dimensions and
facts), and data exposure using Power BI. The recurring keywords (ETL,
ingestion pipelines, Data Factory, Synapse, unit testing, continuous
integration) indicate that the ideal candidate will write and debug processing
code, not be a Power BI report writer or functional analyst. The production
support context requires someone capable of independently diagnosing and
resolving anomalies within a standardized process environment. This is neither
an architect nor a project management role; therefore, candidates with
primarily strategic or decision-making experience should be excluded.

Responsibilities :

• Provide technical support to operations following production
  deployments and follow up on issues with project managers.
  
• Perform solution
  monitoring activities.
  
• Take responsibility for resolving solution anomalies, in
  collaboration with other members of the project team.
  
• Analyze system
  components, functional and non-functional specifications, change requests, and
  any technical issues encountered.
  
• ETL Analysis and Development Configuration of
  data ingestion pipelines from source systems to appropriate data lakes
  Participation in data enhancement and data warehouse configuration
  (dimension/fact configuration) according to the established data model
  Participation in data loading into tables Process breakdown and documentation
  Data profiling (tools, approaches)
  
• Performing unit testing Participating in
  production deployments Ensuring and performing updates to various databases and
  recommending any improvements aimed at optimizing their quality and efficiency.
  
  

Requirements

REQUIREMENTS

• 8+ years of
  hands-on experience as a developer in a large enterprise | Required | All
  requirements met
  
• Excellent
  ETL knowledge and ETL development skills | Required | All requirements met
  
• Source
  system to data lake ingestion pipelines | Required | All requirements met
  
• Relational
  and dimensional models, dimension and fact configuration | Required | All
  requirements met
  
• Azure data
  storage (Data Lake, Blob Storage, Data Factory, Azure SQL Database, Synapse
  Analytics) | List of examples | Sufficient majority
  
• Power BI
  (Desktop, Service, components including gateway) | Required | All requirements
  met
  
• Unit
  testing approaches (TDD), automated testing, and continuous integration | List
  of examples | Sufficient majority
  

DESIRED

• Source code
  management and deployment (GitHub, GitHub Actions, Concourse) | List of
  examples | Sufficient majority
  
• Experience
  in data projects | Required | All requirements met
  
• Architecture
  patterns (Object-Oriented, Cloud IaaS, CaaS, PaaS, SaaS, iPaaS) | List of
  examples | Sufficient majority
  

ASSET

• Domain-Driven
  Design (DDD) | Required | Sufficient majority
  
• Application
  resilience and event-driven architecture | List of examples | Sufficient
  majority
  
• Security
  principles and protocols (SSO, Auth0, SAML, OpenID, JWT, OAuth2, ABAC, RBAC) |
  List of examples | Sufficient Majority
  
• Note: The
  Azure stack is listed as an ecosystem; proficiency in most components with
  concrete projects is considered comprehensive. The absence of a single service
  does not disqualify you.
  

WHAT WE
DON'T WANT

• Profiles of
  Power BI report writers without real experience in ETL development and data
  ingestion.
  
• Profiles of
  functional or BI analysts without experience writing data processing code.
  
• Profiles of
  architects or managers whose recent experience is in business intelligence
  rather than hands-on development.
  
• Profiles of
  data engineers outside of Azure without demonstrated transferability to Data
  Factory and Synapse.
  
• Profiles of
  junior or intermediate profiles with less than 8 years of development
  experience in large companies.
  
• Profiles
  incapable of working independently in production support and accustomed to
  close supervision.