Data Integration Engineer

Smart TechLink Solutions Inc.

Hartford, CT, United States

19 days ago

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Role details

Contract type

Temporary to permanent

Employment type

Full-time (> 32 hours)

Working hours

Regular working hours

Job source

www.careerjet.com

Tech stack

Application Programming Interfaces (APIs) Artificial Intelligence Business Analytics Applications Application Integration Architecture Audit Trail Microsoft Azure Software as a Service Cloud Engineering Databases Data Governance Data Infrastructure Data Integration

+25 more

Extract Transform Load (ETL) Data Mapping Dataspaces Data Structures Data Warehousing Electronic Data Interchange (EDI) Middleware Fault Tolerance Data Streaming Systems Integration Enterprise Data Management Data Logging Enterprise Software Applications Snowflake SOAPAPI Event Driven Architecture Data Lakes Data Lineage Enterprise Integration Integration Frameworks Data Management Api Design Data Pipelines Api Management Databricks

Job description

Own the architecture and design of enterprise data integration and connectivity across source systems and data platforms.
Design and implement integration patterns connecting ERP, financial, operational, SaaS, and enterprise applications to the data ecosystem.
Develop scalable integration architectures supporting batch, near-real-time, real-time, and event-driven data flows.
Design and govern API-based, event-driven, file-based, database, and streaming integration patterns.
Lead integration of ERP and financial systems, including general ledger, accounts payable, accounts receivable, procurement, fixed assets, budgeting, and other finance processes.
Define and maintain source-to-target mappings, transformation rules, canonical models, and integration specifications.
Ensure data is transformed, standardized, validated, and enriched appropriately as it moves across systems.
Establish reusable integration frameworks, patterns, and standards to accelerate onboarding of new data sources.
Work with data architects and engineers to integrate source data into data lakes, data warehouses, lakehouses, and downstream analytical platforms.
Design APIs and event interfaces that enable reliable and scalable data exchange between enterprise systems.
Define integration strategies for cloud and on-premises applications and platforms.
Ensure integrations meet enterprise requirements for security, availability, scalability, performance, auditability, and data quality.
Establish monitoring, logging, alerting, reconciliation, and error-handling mechanisms for critical integrations.
Identify and resolve data integration issues across source systems, pipelines, and downstream platforms.
Collaborate with business and technology teams to understand source-system data structures, business rules, and integration requirements.
Maintain integration architecture documentation, interface specifications, data lineage, and technical standards.
Support modernization initiatives, including migration from legacy integrations to modern API, event-driven, and cloud-native architectures.
Provide technical leadership and guidance to integration engineers and development teams.
Evaluate integration technologies, middleware, API management, messaging, and streaming platforms.

Requirements

Strong experience in enterprise data integration, application integration, and integration architecture.
Proven experience integrating ERP and financial systems with enterprise data platforms.
Strong understanding of API-led and event-driven architectures.
Experience with REST/SOAP APIs, messaging, queues, event streaming, and integration middleware.
Strong knowledge of data mapping, transformation, normalization, validation, and reconciliation.
Experience designing both real-time and batch integration patterns.
Strong understanding of data integration across cloud and on-premises environments.
Experience with modern data platforms such as Snowflake, Databricks, Azure, or comparable technologies.
Experience with ETL/ELT and data pipeline technologies.
Understanding of data governance, security, data quality, lineage, and metadata requirements.
Experience designing highly available and fault-tolerant integration solutions.
Strong analytical and problem-solving skills with the ability to troubleshoot complex data flows.
Ability to translate business requirements into clear technical integration specifications.
Strong communication and stakeholder-management skills.