Data Solutions Engineer

We have an exciting opportunity for a Data Solutions Engineer at Eversheds Sutherland (US) LLP. We are searching for someone who wants to be a valued contributor and member of a talented and dynamic team of lawyers, paralegals and business professionals.

 

The Data Solutions Engineer is a hands-on technical role responsible for designing and delivering secure, reliable, and scalable data integration and automation solutions across the firm. This role enables the firm to move, synchronize, and operationalize data across enterprise systems, Microsoft 365 (including SharePoint), and third-party platforms, while leveraging the firm’s SaaS-based lakehouse and Operational Data Store (Azure SQL) as the central hub for analytics, reporting, operational intelligence, and AI-ready datasets.

 

The Data Solutions Engineer focuses on optimizing how the firm uses its data platform by building durable pipelines, integration patterns, automation, and data-ready structures that support business needs. This includes pushing and pulling data into and out of the lakehouse, improving data accessibility and usability, and designing strategies to integrate additional internal and external data sources.

 

This position blends data integration, SQL engineering, Power Platform development, API and integration engineering, and software engineering practices. The successful candidate will be comfortable working in both low-code and code-first environments and will write business logic and integration code to support supportable, enterprise-grade data solutions.

 

Responsibilities and Duties:

 

Data Integration & Platform Enablement

• Maintains and enhances integrations to ensure the reliable movement, unification, and availability of data supporting reporting, analytics, operational workflows, and AI initiatives.
• Publishes curated and governed datasets from the lakehouse to operational systems, business applications, and reporting tools (including Power BI) to support consistent metrics and shared definitions.
• Partners with system and data owners to recommend improvements to data structures, ingestion patterns, and usage strategies that increase performance, reliability, and usability.
• Collaborates with business stakeholders to understand reporting and operational data needs and translate them into reusable, reliable data flows and datasets.
• Enables self-service reporting by ensuring lakehouse outputs are discoverable, understandable, and consumable across teams.
• Develops integration strategies and implementation plans for onboarding new internal and third-party data sources, balancing speed, governance, and long-term maintainability.

 

Power Platform & Automation Engineering

• Builds and maintains automation workflows that reduce manual effort and improve reliability of data movement, validation, notifications, and operational processes.
• Develops and supports solutions using:
• Power Automate for workflow orchestration, triggers, approvals, scheduled processes, connector-based integrations, and custom connectors.
• Power Apps for data capture applications, operational tools, and lightweight front-end solutions supporting structured data collection and workflows.
• Azure Functions for serverless integration services, scheduled jobs, event-driven synchronization, API endpoints, and transformation services.
• Implements resilient automation patterns including logging, retry logic, alerting, error handling, and operational runbooks.

 

Software Engineering & Code-Based Integration

• Writes integration code and business logic supporting data workflows and system interoperability using Python and other appropriate languages.
• Develops API clients, middleware services, and custom integration logic where connector-based solutions are insufficient or enterprise requirements demand code-first approaches.
• Applies sound software engineering practices including version control, modular design, documentation, code reviews, and maintainable architecture.
• Builds reusable components, templates, and standard patterns to accelerate integration delivery across systems.

 

API & Third-Party Data Source Integration

• Integrates data from external platforms into the lakehouse using REST APIs, vendor SDKs, file-based feeds, webhooks, and secure managed transfer patterns.
• Evaluates third-party platforms for integration feasibility, data quality, authentication constraints, and operational reliability.
• Partners with vendors and internal stakeholders to resolve integration issues and support enhancements to the firm’s data ecosystem.