Data Analyst – Banking Data Ingestion & Reconciliation

Tap Growth ai; Singapore; On-site; SGD 90,000 - 120,000; Full time

Job summary

Tap Growth ai in Singapore is seeking an experienced Data Analyst to optimize banking data ingestion and reconciliation. You will analyze data flows, validate ingestion outcomes, and build lineage documentation.

You will collaborate with Finance, Risk, and Technology teams to implement data quality controls, create dashboards in Power BI, and enable accurate regulatory reporting. A 6+ year track record in data analytics within financial services is preferred.

Qualifications

• Experience with data profiling, validation and reconciliation.
• Ability to translate business requirements into data validation rules.
• Knowledge of Bronze/Silver/Gold data layers is a plus.

Responsibilities

• Perform detailed data profiling, validation, and reconciliation of source data.
• Validate source-to-Bronze ingestion for completeness and integrity.
• Develop and execute reconciliation checks across records, balances and totals.
• Investigate data discrepancies between sources and the target platform.
• Document data lineage, mappings, and reconciliation rules.
• Create dashboards and reports in Power BI to communicate quality metrics.
• Collaborate with Finance, Risk, Regulatory Reporting, and Data Engineering.
• Support testing activities including data validation and SIT/UAT reconciliation.

Skills

Analytical thinking

Attention to detail

Stakeholder communication

Data governance understanding

Education

Degree in Computer Science, Information Systems, DataAnalytics, Finance, Accounting, Engineering

Tools

SQL

Databricks

Apache Spark

Python

Excel

Power BI

Notebook environments

Job description

We're Hiring: Data Analyst – Banking Data Ingestion & Reconciliation!

We are looking for an experienced Data Analyst to join our team in Singapore. The ideal candidate will be responsible for analyzing banking data ingestion processes and ensuring accurate reconciliation. You will play a crucial role in optimizing data workflows and enhancing reporting capabilities to support our business objectives.

Location: Singapore, Singapore
Work Mode: Work from Office
Role: Data Analyst – Banking Data Ingestion & Reconciliation

What You'll Do:

Data Analyst – Banking Data Ingestion & Reconciliation

Role Overview

We are seeking an experienced DataAnalyst with strong banking domain knowledge and hands-on expertise in dataprofiling, validation, andreconciliation, and source-to-target analysis. Therole will focus on ensuring the completeness, accuracy, and integrity of sourcedata ingested into the Bronze layer of the data platform across keybanking domains including Management Accounting, Financial Accounting,Regulatory Reporting, and Transaction Banking.

The successful candidate will work closelywith business, finance, data engineering, and technology teams to identify dataquality issues, validate ingestion outcomes, reconcile source-to-Bronze data,and document data lineage and transformation requirements.

Key Responsibilities

• Perform detailed data profiling, validation, andreconciliation of source data loaded into the Bronze layer.
• Validate source-to-Bronze ingestion for completeness,accuracy, consistency, and integrity.
• Develop and execute reconciliation checks covering recordcounts, balances, control totals, field-level comparisons, duplicates,null values, data types, and business-rule validations.
• Investigate and analyze data discrepancies between sourcesystems and the target data platform.
• Identify root causes of data quality and reconciliation issuesand work with data engineering and source-system teams to resolve them.
• Perform source data analysis across banking domains such as:
  • Management Accounting
  • Financial Accounting
  • Regulatory Reporting
  • Transaction Banking
• Translate business and finance requirements into detailed datavalidation and reconciliation rules.
• Create and maintain source-to-target mappings, data lineagedocumentation, reconciliation evidence, and data quality reports.
• Use SQL, Databricks, Spark, Python, notebooks, and Excelto perform large-scale data analysis and profiling.
• Build dashboards and visualizations using Power BI tocommunicate data quality, reconciliation results, trends, exceptions, andkey metrics.
• Collaborate with Finance, Risk, Regulatory Reporting,Transaction Banking, Data Governance, Data Engineering, and Technologyteams.
• Support testing activities including data validation, SIT/UATreconciliation, defect investigation, and production data verification.
• Ensure data controls and reconciliation processes comply withestablished banking data governance and audit requirements.

Required Experience

• 6 years of experience in data analysis within the banking orfinancial services industry.
• Demonstrated hands-on experience in data profiling andsource-to-target reconciliation, particularly for source-to-Bronze orsimilar raw data ingestion layers.
• Strong domain knowledge in at least one of the following:
  • Management Accounting
  • Financial Accounting
  • Regulatory Reporting
  • Transaction Banking
• Strong understanding of banking data, financial datastructures, accounting concepts, transactional datasets, and data qualitycontrols.
• Experience investigating complex data discrepancies andperforming root-cause analysis.

Technical Skills

• Advanced SQL for querying,profiling, reconciliation, and validation of large datasets.
• Hands-on experience with Databricks and/or Apache Spark.
• Experience working with Databricks notebooks or similarnotebook-based analytical environments.
• Proficiency in Python and/or advanced Excel for dataanalysis, reconciliation, and automation.
• Experience documenting data lineage, source-to-targetmappings, and reconciliation rules.
• Working knowledge of Power BI for dashboarding,reporting, and data visualization.
• Familiarity with modern data lake, lakehouse, or cloud-baseddata architectures would be advantageous.

Key Competencies

• Strong analytical and problem-solving skills.
• High attention to detail, particularly when working withfinancial and regulatory data.
• Ability to analyze large and complex datasets and identify dataanomalies efficiently.
• Strong communication skills with the ability to explain dataissues to both technical and business stakeholders.
• Ability to work collaboratively across Finance, Business, Data,and Technology teams.
• Strong documentation and stakeholder management skills.

Preferred Qualifications

• Degree in Computer Science, Information Systems, DataAnalytics, Finance, Accounting, Engineering, or a related discipline.
• Experience working on large-scale banking data transformation,modernization, or data platform programs.
• Exposure to data governance, data quality frameworks, financialcontrols, or regulatory reporting environments.
• Understanding of medallion architecture and Bronze/Silver/Golddata layers is highly desirable.