Data Analyst
Frisco, TX - USA
Job Summary
Mandatory Areas: Senior Data Analyst Finance FP&A / Planning (BPM) Data Quality & Validation
Must have Skills Data Analyst FP&A/ BPM
Skill 1 7Yrs of Exp Data Analysis FP&A BPM Quality and Validation
Skill 2 7Yrs of Exp SQL Databricks Oracle
Skill 3 5Yrs of Exp in Finance Domain
Must have Skills Data Analyst FP&A/ BPM
Skill 1 7Yrs of Exp Data Analysis FP&A BPM Quality and Validation
Skill 2 7Yrs of Exp SQL Databricks Oracle
Skill 3 5Yrs of Exp in Finance Domain
We are seeking a Senior Data Analyst to support a critical finance transformation initiative by ensuring data accuracy completeness and readiness-especially for the FP&A / Planning (BPM) workstream.
The organization is implementing planning modules (Oracle BPM / EDM / EBPCS) and will feed data from upstream platforms such as Snowflake / Databricks into these systems. This role will focus on vetting and validating upstream and downstream data performing analysis to ensure correctness and partnering closely with the Data Architect to support the RDMP platform goals. This role requires someone senior who can ask the right questions challenge assumptions investigate upstream issues and ensure data truly solves the business problem (single source of truth for finance).
Key Responsibilities
Perform data validation and vetting for FP&A/Planning use cases:
o Validate upstream datasets feeding Oracle planning modules (BPM/EDM/EBPCS)
o Identify mismatches quality gaps reconciliation issues and root causes
Conduct data analysis to ensure accuracy and consistency across domains:
o Compare finance outputs across systems to prevent multiple answers to key metrics (e.g. revenue)
Build and execute data quality checks and validation routines:
o Completeness accuracy timeliness and business rule conformance
Work closely with the Data Architect to support RDMP platform build:
o Provide insights on source data issues and domain definitions
o Support lineage/quality requirements and documentation
Collaborate with FP&A partners and domain stakeholders:
o Translate business expectations into validation rules and test cases
o Ensure the data being delivered aligns to real business outcomes
Investigate upstream issues and coordinate with data engineering teams to fix defects quickly.
Maintain documentation on data definitions validation steps findings and remediation status.
Required Qualifications
7 10 years of experience as a Data Analyst / Senior Data Analyst in enterprise data environments.
Strong experience in data analysis and validation using:
o SQL and analytical techniques
o Data profiling and reconciliation across multiple sources
Strong hands-on exposure to:
o Snowflake
o Databricks
o Azure ecosystem (data services understanding)
Familiarity with Oracle planning modules (BPM / EDM / EBPCS) and/or finance planning data flows.
Strong critical thinking and ability to ask probing questions across upstream/downstream systems.
Preferred Qualifications
Finance domain experience (FP&A Accounting Revenue Tax Treasury) or similar data-intensive domains.
Experience supporting data for forecasting / modeling / ML initiatives (data readiness and quality).
Familiarity with data lineage observability and governance practices.
Key Skills & Competencies
Strong attention to detail; data accuracy-first mindset.
Ability to independently investigate issues and drive closure.
Strong ownership and urgency-bias for action.
Strong stakeholder communication; can bridge business technical teams.
Interview Evaluation Focus
Scenario-based data validation and reconciliation discussions
Demonstrated examples of finding root causes across complex data flows
Ability to challenge upstream issues and define what good data looks like
Practical SQL/data reasoning skills
The organization is implementing planning modules (Oracle BPM / EDM / EBPCS) and will feed data from upstream platforms such as Snowflake / Databricks into these systems. This role will focus on vetting and validating upstream and downstream data performing analysis to ensure correctness and partnering closely with the Data Architect to support the RDMP platform goals. This role requires someone senior who can ask the right questions challenge assumptions investigate upstream issues and ensure data truly solves the business problem (single source of truth for finance).
Key Responsibilities
Perform data validation and vetting for FP&A/Planning use cases:
o Validate upstream datasets feeding Oracle planning modules (BPM/EDM/EBPCS)
o Identify mismatches quality gaps reconciliation issues and root causes
Conduct data analysis to ensure accuracy and consistency across domains:
o Compare finance outputs across systems to prevent multiple answers to key metrics (e.g. revenue)
Build and execute data quality checks and validation routines:
o Completeness accuracy timeliness and business rule conformance
Work closely with the Data Architect to support RDMP platform build:
o Provide insights on source data issues and domain definitions
o Support lineage/quality requirements and documentation
Collaborate with FP&A partners and domain stakeholders:
o Translate business expectations into validation rules and test cases
o Ensure the data being delivered aligns to real business outcomes
Investigate upstream issues and coordinate with data engineering teams to fix defects quickly.
Maintain documentation on data definitions validation steps findings and remediation status.
Required Qualifications
7 10 years of experience as a Data Analyst / Senior Data Analyst in enterprise data environments.
Strong experience in data analysis and validation using:
o SQL and analytical techniques
o Data profiling and reconciliation across multiple sources
Strong hands-on exposure to:
o Snowflake
o Databricks
o Azure ecosystem (data services understanding)
Familiarity with Oracle planning modules (BPM / EDM / EBPCS) and/or finance planning data flows.
Strong critical thinking and ability to ask probing questions across upstream/downstream systems.
Preferred Qualifications
Finance domain experience (FP&A Accounting Revenue Tax Treasury) or similar data-intensive domains.
Experience supporting data for forecasting / modeling / ML initiatives (data readiness and quality).
Familiarity with data lineage observability and governance practices.
Key Skills & Competencies
Strong attention to detail; data accuracy-first mindset.
Ability to independently investigate issues and drive closure.
Strong ownership and urgency-bias for action.
Strong stakeholder communication; can bridge business technical teams.
Interview Evaluation Focus
Scenario-based data validation and reconciliation discussions
Demonstrated examples of finding root causes across complex data flows
Ability to challenge upstream issues and define what good data looks like
Practical SQL/data reasoning skills