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BI / Data / Analytics Lead

From data chaos —
one source of truth.

I design the modern data stack (Snowflake, data mesh on Azure, Power BI) and turn fragmented reporting into governed, self-serve analytics that financial and operational decisions rely on.

See selected work LinkedIn

many scattered sources → one source of truth

ExcelCSVSQLAPIERPe-mail → one model

24 scattered sources → 1 source of truth

01Work

Projects anonymized: sector instead of client names (NDA). Numbers in visuals are illustrative; scale metrics are real.

FMCG / E-commerce

Consolidating fragmented reporting in Snowflake

P: Reporting was fragmented across many inconsistent sources, with no shared metric definitions.
A: I led the end-to-end migration to Snowflake, consolidating data into a single, governed reporting layer.
R: Shared KPI definitions and a single reporting layer for every team.

SnowflakeELTKPI governance

¹ client withheld (NDA) · figures illustrative

FMCG / E-commerce

Data mesh and domain self-serve

P: The central data team was a bottleneck for a growing volume of business requests.
A: I designed a data mesh architecture on Azure, handing data to business domains as a product.
R: Domains moved to self-serve without losing governance or quality.

AzureData meshData quality

¹ client withheld (NDA) · figures illustrative

FMCG / Finance

Power BI for hundreds of recipients and safeguarded payouts

P: Hundreds of recipients and executives needed reliable dashboards, while variable-pay settlement was error-prone.
A: I built automated financial and sales dashboards with per-region RLS, plus a variable-pay reconciliation process.
R: ~600 recipients and ~50 HQ reports on one standard, with payout accuracy safeguarded.

Power BIDAX / RLSReconciliation

¹ client withheld (NDA) · figures illustrative

GenAI / Enablement

Piloting a knowledge agent for analysts

P: Report logic and business rules lived in people’s heads, slowing onboarding.
A: I work with GenAI daily (Power BI Copilot) and am piloting a Copilot 365 knowledge agent that captures report logic.
R: Pilot in progress. Goal: report knowledge on demand and faster onboarding.

Power BI CopilotCopilot 365MCP

¹ client withheld (NDA) · figures illustrative

Banking

Controls governing transaction-code integrity

P: Transaction-code consistency across global systems required tight oversight.
A: I built controls and tooling governing transaction-code integrity, with automation in MS Access and VBA.
R: Transaction-code consistency under continuous, automated control.

MS AccessVBAControls

¹ client withheld (NDA) · figures illustrative

Financial Crime / AML

Fewer false positives in transaction monitoring

P: Monitoring scenarios generated too many false positives, burdening the team.
A: I tuned AML scenarios (detection indicators and parameters) for precision.
R: Fewer false positives; the team’s attention on genuinely material cases.

AMLTransaction monitoringScenario tuning

¹ client withheld (NDA) · figures illustrative

02Capabilities

The full data stack: from architecture and modeling, through governance and quality, to the presentation layer and automation.

model

A star schema: a fact table with shared dimensions. The foundation of a fast, maintainable semantic model.

Revenue YoY %.dax

Revenue YoY % =
VAR _cur = [Total Revenue]
VAR _prior =
    CALCULATE (
        [Total Revenue],
        SAMEPERIODLASTYEAR ( 'Date'[Date] )
    )
RETURN
    DIVIDE ( _cur - _prior, _prior )

DAX in practice: readable, optimized measures using VAR/RETURN instead of costly iteration.

Data platform

SnowflakeAzure (data mesh)ETL / ELTSQLLayered architecture

Semantic modeling

Dimensional modelingDAXPower Query (M)Tabular EditorRLSPerformance tuning

Governance & quality

KPI governanceData qualityReconciliationDocumentation

Reporting & UX

Power BIFinance/sales dashboardsExecutive reportingFigma (UX)

AI & automation

GenAI / LLMPower BI CopilotMCPPower AutomateAlteryxVBA

Tools

Advanced ExcelPythonJiraAgile

03By the numbers

The scale I work at

The scale of the deployments I led.

EXP

~10 yrs

in BI and data analytics

TEAM

10 people

analytics team under my lead

REACH

~600

dashboard recipients in one organization

EXEC

~50

reports dedicated to executives and HQ

04Process

How I work: from the first business question to a report you can trust.

01

Decision first, data second

I start from the question a report must answer — not from whatever tables exist.

02

A shared data layer

I consolidate fragmented data into a single layer with shared metric definitions and clear governance.

03

Performance and correctness

I tune models so reports are fast and the numbers reconcile to the cent.

04

Self-serve and documentation

I hand teams the tooling and procedures that let analytics scale without a bottleneck.

05About

I’m a BI/Data leader with around ten years across banking, fintech, FMCG, and e-commerce. I combine modern-data-stack architecture with ownership of one thing above all: that the numbers are correct and the reports get used.

I led a ten-person analytics team in Agile delivery, partnering with Finance, Sales, and executives. I owned a migration to Snowflake, a data mesh design on Azure, and Power BI rollouts for hundreds of recipients.

I apply GenAI daily to assist analytical work, and as an active Power BI trainer (previously a corporate Excel trainer) I translate complex data topics into language executives act on.

Contact

Let’s talk data.

Looking for someone to bring order to your analytics and build reports your executives trust? Write to me — I reply within 24 hours.

Available — senior projects / roles

e-mail LinkedIn