Senior Data Engineer

Womble Bond Dickinson (US) LLP is seeking a remote Senior Data Engineer to their US team. The Senior Data Engineer is the Firm's hands-on technical owner for its enterprise internal data platform as it moves from a long-established SQL Server data warehouse and reporting environment to Microsoft Fabric. The role keeps the current environment reliable through the transition, works alongside the Firm's implementation partner to take ownership of the new platform, and puts in place the engineering discipline that a platform supporting financial, compensation, and performance reporting requires. Over time, the role leads data engineering for changes to the Firm's core business system.

RESPONSIBILITIES :

• Operate the Firm's Microsoft Fabric data platform day to day: monitor nightly orchestration and refreshes, triage and resolve failures, restart processing from the point of failure, track capacity use and cost, confirm data is complete before business users rely on it, and keep business owners informed when issues arise. • Audit and reconcile financial data throughout development: trace accounting transaction flows (time entry, billing, cash receipts, and general ledger postings) from source systems through the legacy warehouse and Fabric; build and run reconciliation and data quality checks (row counts, key coverage, and financial totals); investigate, explain, and document inconsistencies; and protect exact-output requirements for compensation and financial close reporting. • Work alongside the Firm's implementation partner through the remaining migration phases: pair on converting SQL Server stored-procedure logic to Fabric notebooks (PySpark and Spark SQL), review converted logic for fidelity to existing business rules, and take ownership of each component as knowledge transfer is completed. • Design, build, and maintain ingestion and transformation pipelines across the bronze, silver, and gold layers, including database mirroring and metadata-driven copy pipelines from on-premises SQL Server, slowly changing dimensions, and incremental loading for the largest fact tables once migrated outputs are reconciled. • Implement and maintain data-level security, including Microsoft Entra group-based workspace and item permissions, OneLake security, row- and object-level security, column-level security and data masking, and Purview sensitivity labels, so that compensation, payroll, HR, personal, and client billing data is available only to authorized users, whatever tool they use to reach it. • Maintain Direct Lake semantic models with the BI team (relationships, DAX measures, calculation groups, security roles, and Excel connectivity) and support the move of reporting from SSAS and SSRS to Power BI. • Apply disciplined engineering practices to all data platform code: Git source control and peer review in Azure DevOps, CI/CD promotion from development to test to production, automated testing, secrets management, and current documentation of data models, source-to-target mappings, dependencies, and runbooks. • Prepare curated, documented, and secured data and semantic models for analytics and AI-assisted access (for example, Microsoft Copilot and Fabric data agents), and support the Firm's AI and automation initiatives with governed access to that data. • Support the legacy SQL Server environment (staging and warehouse databases, SQL Agent jobs, replication, SSAS tabular models, and SSRS reports) while it remains in service; log and assess changes for their effect on the Fabric platform; re-point downstream feeds; and retire components once their replacements are signed off. • Maintain data feeds from the Firm's business systems (financial management, CRM, HR and payroll, and others) and lead the data engineering work for planned changes to core business systems, including data mapping, conversion validation, and continuity of historical reporting.