Finance Data Engineer

SPR Consultech

Empowering Finance through Data, AI, and Digital Transformation

Job Title: Finance Data Engineer

Department - Finance Transformation & Digital Tower

Location -

Reports To -

Experience -

About SPR Consultech

At SPR Consultech, we are reimagining the intersection of finance, technology, and transformation. With a footprint across the globe our multidisciplinary team helps enterprises and CFO offices modernize their finance operations through data engineering, automation, and AI-driven insights. We are now expanding our Digital Finance Tower and seeking passionate individuals who blend deep finance domain understanding with data and software engineering excellence.

Role Overview

As a Finance Data Engineer, you will architect and automate the financial data backbone that powers decision intelligence across multiple business units and geographies. You’ll collaborate with finance leaders, analysts, and data scientists to design data pipelines, APIs, and dashboards that unlock real-time visibility, efficiency, and compliance in financial ecosystems.

Key Responsibilities

Data Architecture & Pipeline Engineering

·      Build and maintain robust financial data pipelines using Python, SQL, and ETL frameworks.

·      Automate data ingestion and transformation from ERPs (Zoho Books, SAP, QuickBooks, Xero, Tally).

·      Implement data quality, reconciliation, and validation mechanisms ensuring accuracy and compliance.

·      Optimize schema design for analytics, reporting, and forecasting workflows.

Finance Data Automation

·      Develop Python-based automations for journal entries, reconciliations, and report generation.

·      Integrate finance data from multiple systems (ERP, payroll, compliance, and tax platforms).

·      Maintain standardized data models for P&L, Balance Sheet, Cash Flow, and Working Capital metrics.

·      Enable real-time CFO dashboards and predictive analytics feeds.

Analytics & AI Enablement

·      Partner with FP&A and Audit teams to curate analytical datasets for cost analysis, forecasting, and performance tracking.

·      Support the deployment of AI/ML-driven financial insights (cash flow forecasting, anomaly detection, etc.).

·      Collaborate with BI engineers to build Power BI, Zoho Analytics, or Streamlit dashboards.

DevOps & Cloud Collaboration

·      Deploy workflows using Docker, Airflow, Portainer, or serverless functions.

·      Manage CI/CD pipelines for financial data scripts with GitHub Actions or GitLab.

·      Optimize cloud storage and compute (AWS S3, RDS, Glue | GCP BigQuery, Cloud Composer).

Governance & Documentation

·      Maintain data lineage, metadata, and cataloging standards.

·      Ensure compliance with IFRS, GAAP, and statutory frameworks.

·      Prepare technical documentation, process maps, and audit-ready data dictionaries.

Required Skills

Finance Domain Expertise

·      Strong grasp of financial accounting, FP&A, and management reporting.

·      Experience handling ERP financial modules (GL, AR, AP, FA, Payroll).

·      Working knowledge of tax and compliance data structures (GST/VAT, statutory filings).

Technical Proficiency

·      Programming: Python (pandas, numpy, requests, pyodbc, openpyxl, FastAPI).

·      Databases: MySQL, PostgreSQL, SQL Server, BigQuery.

·      ETL & Orchestration: Airflow, NiFi, Prefect (or similar).

·      Visualization: Power BI, Zoho Analytics, Streamlit, Dash.

·      APIs & Integrations: REST, JSON, OAuth2.

·      Version Control: Git, GitHub, CI/CD workflows.

·      Cloud: AWS / GCP for data storage and compute.

Preferred / Nice-to-Have

·      Experience with Zoho Finance Suite, Oracle, SAP FICO, or QuickBooks APIs.

·      Exposure to AI/ML finance models (forecasting, scoring, anomaly detection).

·      Familiarity with data governance and catalog tools (Alation, Collibra, or open-source).

·      Experience in containerized deployments and finance analytics microservices.

Qualifications

·      Bachelor’s / Master’s degree in Finance, Computer Science, Data Engineering, or related field.

·      3–8 years of experience in Finance Data Engineering, FP&A Automation, or Finance Analytics.

·      Certifications such as CFA, CPA, or AWS Data Engineering are advantageous.

Behavioural & Cultural Fit

·      Analytical thinker with attention to detail and problem-solving capability.

·      Ability to translate finance problems into data solutions.

·      Strong communication and teamwork across finance and tech functions.

Driven by purpose — aligned with SPR’s 'Right to Dream' culture of innovation and transformation.