Finance Technology Data Solutions Engineer in Haciendas del Canada, Nuevo León at Jobgether

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Finance Technology Data Solutions Engineer based in Canada.

This role offers the opportunity to build and support data solutions powering fund accounting, investment operations, and financial reporting for a US-based asset management environment. You will work across data integrations, transformations, reconciliations, controls, and data products that support critical financial processes. The position requires strong hands-on expertise with Databricks, Python, PySpark, and SQL to process and manage large-scale financial data. You will apply your understanding of fund accounting, investment data, and financial services to deliver reliable and well-controlled solutions. Working as an individual contributor, you will collaborate directly with US stakeholders and contribute to data engineering initiatives in a regulated environment. The role is available on a part-time or full-time remote basis.

• Build, maintain, and support data solutions for fund accounting, investment operations, and finance reporting.
• Develop data integrations, transformations, pipelines, and data products using Databricks, Python, PySpark, and SQL.
• Implement and maintain financial data reconciliations, controls, and validation processes.
• Work with fund accounting processes including NAV calculation, accruals, corporate actions, fees, and month-end close.
• Process and integrate investment data covering positions, transactions and trades, security master data, pricing, cash, and general ledger information.
• Optimize complex SQL queries, data pipelines, and large-scale processing workloads for performance and reliability.
• Work with cloud-based data platforms and support scalable data engineering solutions.
• Collaborate directly with US-based stakeholders to understand requirements and deliver effective data solutions.
• Contribute to data quality, testing, CI/CD, and operational improvements across financial data pipelines.

Requirements:

• 10+ years of hands-on data engineering experience, with a strong individual contributor focus rather than team leadership or architecture.
• Strong, recent hands-on experience with Databricks, including Delta Lake, notebooks, jobs, and workflows; Unity Catalog experience is preferred.
• Strong understanding of fund accounting processes, including NAV calculation, accruals, corporate actions, fees, and month-end close.
• Advanced Python and PySpark skills for large-scale data processing.
• Proven experience delivering data solutions within Financial Services, with Asset Management, Investment Management, Fund Administration, Custody, or Capital Markets experience strongly preferred.
• Experience developing reconciliations and data controls within financial or regulated environments.
• Strong understanding of investment data, including positions, transactions, security master, pricing, cash, and general ledger data.
• Expert SQL skills, including complex joins, window functions, and performance tuning.
• Experience with at least one cloud platform, such as Azure or AWS.
• Strong written and spoken English, with confidence communicating directly with US stakeholders.
• Databricks Data Engineer or Azure/AWS data engineering certification is a plus.
• Experience with Azure Data Factory, Airflow, Databricks Workflows, or Fivetran is beneficial.
• Familiarity with Snowflake, dbt, Power BI, or Tableau for downstream reporting is a plus.
• Experience with Git, Azure DevOps, GitHub Actions, CI/CD, and unit testing for data pipelines is beneficial.
• Finance Management and a BE, BTech, or MCA qualification are advantageous.

Benefits:

• Fully remote working model.
• Part-time or full-time employment options.
• Opportunity to work on financial data solutions supporting fund accounting and investment operations.
• Direct collaboration with US-based stakeholders.
• Exposure to Financial Services and asset management data environments.
• Hands-on work with Databricks, cloud data platforms, Python, PySpark, and modern data engineering technologies.
• Opportunity to contribute to data solutions involving reconciliations, controls, reporting, and regulated financial processes.