Senior Data Analyst - Finance and Accounting

8 years

0 Lacs

Posted:1 day ago| Platform: Linkedin logo

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On-site

Job Type

Full Time

Job Description

Senior Data Analyst (Finance & Accounting)


About the Role

We’re looking for a Senior Data Analyst to turn large, messy financial datasets into clear, actionable insights. You’ll partner with Finance, Accounting, and Engineering to design robust analyses, build decision-ready dashboards, and drive reconciliation accuracy across bank files, GL feeds, and sub-ledgers.

What You’ll Do
  • Own analytics for finance workflows:

    Depository Account Reconciliation (DAR), AP/AR, Daily Income Journal (DIJ), revenue recognition, month-end close, variance analysis.
  • Data wrangling & modeling:

    Ingest, clean, and model data from BAI/BAI2 bank files, GL (Oracle/Yardi/MRI/NetSuite), PMS/ERP exports, payment gateways, and data lakes.
  • EDA → inference:

    Frame hypotheses, run exploratory/statistical analyses, and deliver clear narratives with quantified impact (trends, anomalies, outliers, correlations).
  • Reconciliation analytics:

    Build matching logic (exact/fuzzy/multi-key), exception buckets, and root-cause drill-downs for unmatched transactions.
  • Metrics & dashboards:

    Define and publish finance KPIs (auto-match %, write-offs, DSO, unapplied cash, exceptions aging) via curated semantic layers and BI dashboards.
  • Data quality stewardship:

    Establish checks, controls, and monitoring (balance checks, duplicate detection, schema drift, completeness/timeliness tests).
  • Stakeholder enablement:

    Translate CFO/Controller questions into analysis plans; document assumptions; present findings to execs with crisp recommendations.
  • Automation partnership:

    Collaborate with data engineering to productionize repeatable pipelines, models, and audits; create specs for dbt/ETL jobs.
  • Compliance-aware analysis:

    Ensure work products support

    SOX

    controls and align with

    US GAAP

    ; maintain reproducible, auditable notebooks and artifacts.
Must-Have Qualifications
  • 5–8+ years in data analysis/analytics (at least 3 years in

    Finance/Accounting

    analytics).
  • Strong SQL

    (window functions, CTEs, query optimization) and

    Python

    (pandas, NumPy; statsmodels/scikit-learn for light modeling).
  • Proven experience with

    GL/AP/AR

    data, bank statement structures (e.g.,

    BAI/BAI2

    ), and reconciliation/matching logic.
  • Hands-on with a modern BI tool (Power BI / Tableau / Looker / Superset) and version-controlled analytics (git).
  • Excellent storytelling: converts ambiguous business questions into testable analyses and executive-friendly outputs.
  • Solid grasp of accounting concepts (journal entries, trial balance, revenue vs. receipts, accruals/deferrals) and

    controls mindset

    .
Nice to Have
  • dbt, Airflow/Prefect, Dagster; Snowflake/BigQuery/Redshift; AWS (S3, Glue, Athena, Lambda).
  • Experience with

    anomaly detection

    , fuzzy matching (record linkage), and rule-based + ML hybrid matching.
  • Familiarity with

    SOX

    ,

    GAAP

    , audit evidence, and finance close calendars.
  • Exposure to payments/settlement data, PMS/ERP integrations, or RPA/agentic automations.
  • Basic proficiency with GitHub Actions/CI for analytics artifacts.


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