Blend360
Tech / AI / Software
SrDataEngineeringManager
Neural analysis suggests this role is
optimal for mid candidates.
“Sr Data Engineering Manager at Blend360. Skills: Data Engineering, Cloud Integration, Azure, Databricks, SQL, Python, Data Transformation, Data Pipelines. Establish and validate connections to in-scope enterprise source systems. Conduct data profiling across source systems”
Industry & Context.
What They're Looking For.
Must Have
7+ years of experience in data engineering, hands-on delivery in cloud-based integration or analytical environments, experience connecting to enterprise application APIs and databases, REST, SOAP/XML, JDBC/ODBC, file-based extraction patterns, Proficiency in SQL, Proficiency in Python for data transformation, cleansing, and validation, Experience building and maintaining data pipelines on Azure, Hands-on experience with Databricks or a comparable cloud lakehouse platform, working within a layered data architecture (Bronze/Silver/Gold or equivalent), Experience with dbt (Core or Cloud) for SQL-based transformation and data modelling within a lakehouse environment, Understanding of data mapping, canonical data modelling, transformation design for multi-system integration landscapes, Experience working to build-ready technical specifications, contributing to formal design and testing processes within a structured delivery programme
Nice to Have
Familiarity with enterprise MDM platforms, experience preparing or loading master data for Customer, Supplier, or Employee domains, Experience with Azure Service Bus or event-driven integration patterns, an understanding of how data engineering fits within a broader pub/sub architecture, Exposure to data governance tooling including Unity Catalog or equivalent for access control, lineage, and data cataloguing, Familiarity with data quality testing approaches, experience implementing automated validation checks within pipelines, Background in facilities management, field services, or similarly complex multi-system enterprise environments, Experience contributing to operational handover documentation, including pipeline runbooks and data dictionary maintenance
What You'll Do.
Establish and validate connections to in-scope enterprise source systems
Conduct data profiling across source systems
Design and implement the data transformation logic within integration adapters
Build and maintain reusable transformation components
Implement data validation rules within adapters
Build and maintain batch ingestion pipelines from in-scope source systems into the client's Databricks-based data platform
Configure pipeline orchestration
incremental load patterns
Implement data quality checks within the ingestion pipeline
Design and implement data feeds between source systems and the enterprise MDM platform
Support the reference data wave by preparing and loading initial reference datasets into the MDM platform
How You'll Work.
Team & Collaboration
Working alongside. NET Integration Engineers; collaborate with solution architects and the MDM workstream; Work closely with. NET Integration Engineers to ensure the data layer of each adapter is consistent with the approved integration design
Communication Scope
communication skills; ability to engage with both technical and business stakeholders on data quality and mapping decisions
Process & Methodology
structured delivery programmes, formal design and testing processes within a structured delivery programme
Full Job Description
Blend is a premier AI services provider, committed to creating meaningful impact for its clients through the power of data science, AI, technology, and people. We help organisations solve complex business challenges by combining deep domain understanding with modern data and AI capabilities. Our teams work across strategy, analytics, engineering, and product delivery to create scalable, high-value solutions that improve decision-making, efficiency, and growth. We are looking for an experienced Data Engineer to support the delivery of a large-scale enterprise systems integration programme for a leading facilities management client. Working alongside .NET Integration Engineers, you will be responsible for the data layer of the integration, connecting to source systems, profiling and transforming data, and ensuring clean, well-structured payloads flow through the event-driven Azure Integration Hub. In addition to adapter-level data work, you will build batch ingestion pipelines into the client's Databricks-based data platform and help establish the data interfaces required for the enterprise MDM implementation. The ideal candidate combines strong hands-on data engineering skills with practical experience connecting to complex enterprise application landscapes and working within structured delivery programmes. Responsibilities Source Connectivity & Data Profiling * Establish and validate connections to in-scope enterprise source systems spanning HR, payroll, recruitment, ERP, CRM, procurement, CAFM, field service, fleet, and QHSE platforms, covering a range of connectivity patterns including REST APIs, SOAP/XML, database connectors, and file-based extracts * Conduct data profiling across source systems to assess data quality, volumes, formats, and structures, documenting findings and working with business stakeholders to define and implement automated data quality tests * Identify and escalate data quality issues that could impact integration or MDM readiness, and track
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