Financial Data Analyst

Job highlights

• Experience in SQL, Python, data transformation, financial reconciliations, and working with large financial datasets
• Develop and optimize data pipelines, perform data validation and reconciliation, prepare financial reports and dashboards, collaborate with Finance and IT teams, and automate reporting workflows

Job Description Data Engineer (Finance & Analytics)

About the Role

We are looking for a skilled Data Engineer Finance & Analytics to work on financial data processing, data pipeline development, data validation, reporting, and analytics solutions within the pharmaceutical industry.

The ideal candidate should have experience in SQL, Python, data analysis, data transformation, and working with large volumes of financial or business data. Knowledge of Databricks, PySpark, Azure cloud services, financial reconciliations, and reporting tools will be an added advantage.

Key Responsibilities

* Develop, maintain, and optimize data pipelines for financial and business data.

* Extract, transform, validate, and analyze large datasets from multiple sources.

* Perform data reconciliation and investigate discrepancies between source systems and financial records.

* Develop SQL queries, Python scripts, and automated data processing workflows.

* Prepare financial reports, dashboards, and analytical summaries for business stakeholders.

* Ensure data accuracy, consistency, quality, and integrity across systems.

* Work with cloud-based data platforms and data warehousing solutions.

* Collaborate with Finance, IT, and business teams to understand data requirements.

* Identify process improvements and automate repetitive reporting activities.

* Maintain technical documentation and follow data governance and security standards.

Required Skills

* Strong knowledge of SQL and data analysis.

* Experience with Python and data transformation.

* Understanding of ETL/ELT processes and data pipeline development.

* Experience working with large datasets and data validation.

* Strong analytical, problem-solving, and reconciliation skills.

* Advanced Excel skills, including PivotTables, lookups, and data analysis.

* Good communication and stakeholder management skills.

Preferred Skills

* Hands-on experience with Databricks, PySpark, and Apache Spark.

* Knowledge of Microsoft Azure, Azure Data Factory, and cloud data platforms.

* Experience with Power BI and dashboard development.

* Understanding of Delta Lake, Lakehouse architecture, and data governance.

* Exposure to pharmaceutical financial data, rebates, allowances, or Gross-to-Net (GTN) processes.

* Experience with ERP systems such as NetSuite.

* Knowledge of Git, CI/CD, and workflow orchestration tools.