[Job-31838] Senior Data Analyst (Data Quality & Reporting), Brazil
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What you'll do
- Build and maintain Azure Data Factory pipelines, ingestion flows, and Bronze layer data contracts under the Data Engineer Lead's direction
- Manage source system integration points: Infor SyteLine, Infor ION, Dynamics CRM, Workday, OneStream, and Fusion PLM
- Ensure pipeline reliability, SLA compliance, and incident response for all ingestion flows
- Apply platform standards and CI/CD practices established by the Core Team's Data Architect
- Support Bronze schema definition and validation
- Support ingestion pipeline architecture design in partnership with the Data Engineer Lead
- Escalate and troubleshoot incidents affecting pipeline reliability
What they're looking for
- Azure Data Factory pipeline development experience
- Azure Synapse Analytics experience
- Solid SQL skills
- Experience integrating ERP or CRM source systems into a data pipeline
- Medallion Architecture/Bronze-Silver-Gold Architecture: Familiarity with Bronze-layer data contracts and CI/CD practices for data pipelines
- Advanced English
Nice to have
- Python experience
- Databricks or Spark experience
- Experience with Infor ION integration specifically
- Familiarity with pipeline monitoring and observability tools
Summarised by NextRaise from the employer’s description, which follows in full below.
Full description from employer
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).
• Comfortable working with financial/accounting data and 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.
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.
• Experience with a cloud data warehouse (Snowflake preferred).
• Experience in mortgage, lending, or financial-services reporting.
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