Client Implementation Engineer

About our client

Our client is a tax technology company building an AI-powered platform that automates corporate income tax work for large enterprises. It covers the ASC 740 provision through the disclosures public companies file, including the new ASU 2023-09 income tax disclosures and Pillar Two (GloBE) workflows. The platform connects to ERP and provision systems such as SAP, Oracle and ONESOURCE, and keeps a tax professional in the loop on every AI-assisted change to a tax computation. It was founded by senior corporate tax practitioners; its customers are enterprise tax departments, typically Fortune 500 scale.

About the roleYou will be the engineer who turns a new client's tax data into a working implementation of the platform. Every client arrives with trial balances, legal-entity structures, provision workpapers, ERP extracts and years of spreadsheets. You own getting that data in, validated and reporting correctly, and handing the client's tax team a system they trust.

This is a hands-on, client-facing engineering role: part data engineer, part solutions consultant. You will write the scripts, build the reports and sit in the working sessions with client tax teams. You will work alongside the product team and tax subject-matter experts, and you will shape how implementations are run as the company grows.

What you'll do

• Own the technical side of client onboarding from kickoff to go-live: map the client's trial balances, entity hierarchies, book-tax differences and provision workpapers to the platform's data model.
• Write Python scripts to extract, clean, reconcile and load client data from ERP exports (SAP, Oracle), provision tools (ONESOURCE Tax Provision and similar) and Excel workbooks.
• Build validation checks that catch tie-out, completeness and mapping issues before the client or their auditors do.
• Build HTML reports and dashboards, such as reconciliation summaries, data-quality reports and client-ready outputs, that tax teams can read without a developer.
• Work fluently in Excel: reverse-engineer client workbooks, audit formulas, pivot and reconcile large datasets, and produce clean Excel deliverables when that is what the client needs.
• Turn one-off implementation scripts into reusable tooling and templates so each implementation gets faster than the last.
• Act as the technical point of contact for client tax teams during implementation: run working sessions, document requirements, troubleshoot data issues and explain technical choices in plain language.
• Feed recurring data problems, integration gaps and feature requests back to product and engineering.

What we're looking for

• 3+ years in an implementation, solutions, data or analytics engineering role, ideally for an enterprise SaaS product or in financial systems.
• Strong, practical Python for data work: pandas or equivalent; parsing CSV, Excel, XML and JSON; calling APIs; querying databases; and writing scripts other people can run and maintain.
• Able to build reports in HTML and CSS (templating with Jinja or similar, simple charts). You do not need to be a front-end engineer, but your output should look professional and work in any browser.
• Solid Excel: lookups, pivots, structured references, data cleaning and large-workbook hygiene; able to follow and debug someone else's model.
• Working SQL.
• A reconciler's mindset: you notice when numbers do not tie, and you do not move on until you know why.
• Clear written and spoken communication with finance and tax professionals who are not technical.
• Comfortable with ambiguity: early-stage company, enterprise clients, evolving product.

Nice to have

• Exposure to corporate tax or accounting: ASC 740 and the income tax provision, tax compliance, general ledger and trial balance structures, or the financial close.
• Hands-on experience with a provision or compliance platform such as ONESOURCE, Corptax, Longview Tax or Oracle TRCS.
• ERP data experience (SAP, Oracle, NetSuite, Workday): charts of accounts, entity hierarchies, GL extracts.
• Familiarity with XBRL or SEC financial reporting.
• Git, basic cloud (AWS, Azure or GCP) and experience with workflow or low-code automation tools.
• A background in Big Four tax technology, finance systems or FP&A.