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Define and run data quality checks and reconciliations against approved Finance benchmarks
Validate migrated reports and dashboards for parity with legacy output, including parallel runs
Investigate data quality issues and reconciliation variances with Data Engineering
Build and maintain Power BI data quality dashboards for Finance stakeholders
Produce acceptance evidence and sign-off packages for each delivery gate
Define and run data quality checks and reconciliation logic against the curated data layer, comparing results to approved Finance benchmarks and closed accounting periods
Validate migrated and re-pointed reports and dashboards for parity against their prior legacy-source output, including parallel-run comparisons during cutover
Profile and investigate data quality issues and reconciliation variances, working with Data Engineering to identify and document root cause
Build and maintain data quality dashboards/reports in Power BI (or the equivalent BI tool)
Produce the acceptance evidence — reconciliation results, parallel-run comparisons, sign-off packages — required at each delivery gate, including the cutover gate
Solid experience as a data analyst or BI analyst, with strong hands-on SQL for querying, validating, and reconciling data. • Hands-on experience building or validating reports/dashboards in Power BI or a comparable enterprise BI tool. • Experience with a data-quality or reconciliation framework or methodology (e.g. dbt tests, Great Expectations, or a structured manual reconciliation practice). • Experience with data in the financial/accounting domain, FP&A or Mortgage, including closed-period reconciliation constraints. • Strong attention to detail and clear written documentation of data quality findings. • Fluent English (B2) — coordinates quality findings and evidence directly with client stakeholders at delivery gates. • Hands-on experience with Snowflake.
Experience with financial/GL reporting domains (chart of accounts, dimensions, close process). • Experience validating report or dashboard migrations off a legacy source system onto a new platform.
From the employer’s posting.
At CI&T, our rapid growth is fueled by the innovative solutions we create for our global clients.
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Actively hiringFirst seen by us 6 days ago, still listed, and not a repost of an earlier posting.
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Day 6
Similar jobs usually come down between day 5 and day 41.
From 10,535 similar postings that came down. Coming down is not always a hire.
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Requirements: • Solid experience as a data analyst or BI analyst, with strong hands-on SQL for querying, validating, and reconciling data. • Hands-on experience building or validating reports/dashboards in Power BI or a comparable enterprise BI tool. • Experience with a data-quality or reconciliation framework or methodology (e.g. dbt tests, Great Expectations, or a structured manual reconciliation practice). • Experience with data in the financial/accounting domain, FP&A or Mortgage, including closed-period reconciliation constraints. • Strong attention to detail and clear written documentation of data quality findings. • Fluent English (B2) — coordinates quality findings and evidence directly with client stakeholders at delivery gates. • Hands-on experience with Snowflake. Nice to Have:
Responsibilities: • Define and run data quality checks and reconciliation logic against the curated data layer, comparing results to approved Finance benchmarks and closed accounting periods. • Validate migrated and re-pointed reports and dashboards for parity against their prior legacy-source output, including parallel-run comparisons during cutover — running old and new side by side and confirming they tie out within agreed tolerance. • Profile and investigate data quality issues and reconciliation variances, working with Data Engineering to identify and document root cause. • Build and maintain data quality dashboards/reports in Power BI (or the equivalent BI tool) so quality status and known variances stay visible to Finance and delivery stakeholders on an ongoing basis. • Partner with Finance and business stakeholders to define acceptance criteria and quality thresholds for each reporting deliverable. • Produce the acceptance evidence — reconciliation results, parallel-run comparisons, sign-off packages — required at each delivery gate, including the cutover gate. • Document data quality rules and known issues in a form the client's own team can maintain post-handoff. Requirements:
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At CI&T, we help large enterprises transform the potential of AI into real business impact with AI Deployment, AI-native execution, and tech-integrated business solutions.
With 30 years of experience in technological transformation, we accelerate innovation with expertise in Agentic SDLC, Application modernization, Data & AI, Martech and Business strategy.
We are 8,000 CI&Ters across more than 25 countries, collaborating to build solutions with real impact. AI is already part of how we work, evolve, and innovate every day.
About Us:
At CI&T, our rapid growth is fueled by the innovative solutions we create for our global clients. We are seeking a Data Analyst with a focus on data quality and reporting for a large-scale Finance data platform modernization at a major US mortgage lender — making sure the curated data and reports built on the new platform are correct and tie out to trusted Finance benchmarks. Pipeline-level monitoring and CI/CD are owned by the DataOps Engineer; this role is about the data and the numbers, not the pipeline mechanics.
Responsibilities:
• Define and run data quality checks and reconciliation logic against the curated data layer, comparing results to approved Finance benchmarks and closed accounting periods.
• Validate migrated and re-pointed reports and dashboards for parity against their prior legacy-source output, including parallel-run comparisons during cutover — running old and new side by side and confirming they tie out within agreed tolerance.
• Profile and investigate data quality issues and reconciliation variances, working with Data Engineering to identify and document root cause.
• Build and maintain data quality dashboards/reports in Power BI (or the equivalent BI tool) so quality status and known variances stay visible to Finance and delivery stakeholders on an ongoing basis.
• Partner with Finance and business stakeholders to define acceptance criteria and quality thresholds for each reporting deliverable.
• Produce the acceptance evidence — reconciliation results, parallel-run comparisons, sign-off packages — required at each delivery gate, including the cutover gate.
• Document data quality rules and known issues in a form the client's own team can maintain post-handoff.
Requirements:
• Solid experience as a data analyst or BI analyst, with strong hands-on SQL for querying, validating, and reconciling data.
• Hands-on experience building or validating reports/dashboards in Power BI or a comparable enterprise BI tool.
• Experience with a data-quality or reconciliation framework or methodology (e.g. dbt tests, Great Expectations, or a structured manual reconciliation practice).
• Experience with data in the financial/accounting domain, FP&A or Mortgage, including closed-period reconciliation constraints.
• Strong attention to detail and clear written documentation of data quality findings.
• Fluent English (B2) — coordinates quality findings and evidence directly with client stakeholders at delivery gates.
• Hands-on experience with Snowflake.
Nice to Have:
• Experience with financial/GL reporting domains (chart of accounts, dimensions, close process).
• Experience validating report or dashboard migrations off a legacy source system onto a new platform.
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