Data Engineering & BI
Live updates, transactions, exports and dashboards that stay correct when many people use them at once.
Pipelines, warehouses, and dashboards that turn raw operational data into decisions. Snowflake and Spark where scale demands it, Power BI for the people who read the numbers. We build the plumbing and the picture.
PythonSnowflakeSparkETLPowerBI
TYPICAL TIMELINE · 4–10 WEEKS/01 · SOUNDS FAMILIAR?
When this is the fix
/01Your reports live in Excel and one person knows how they work.
/02Every department has numbers — none of them match.
/03Decisions wait days for data that already exists.
/02 · WHAT'S INCLUDED
What we do
01ETL & data pipelinesData out of tools, spreadsheets, and databases into one reliable flow.
02Dashboards & reportingDashboards people actually open — one source of truth per metric.
03Data models & warehousesSchemas that keep every department's numbers matching; a warehouse when volume earns it.
04Reporting automationThe Monday-morning report that builds itself.
05Operational analyticsProduction tracking, order analytics, attendance summaries — wired into the daily workflow.
06Data qualityValidation and checks that catch bad data before it reaches a decision.
/03 · PROOF
ALL CLIENT WORK →Shipped with this
/04 · EVERY ENGAGEMENT
HOW WE WORK →What you get
/01The repositoryClean, documented code — yours from day one, full commit history included.
/02CI/CD pipelineAutomated build, test, and deploy. Shipping doesn't depend on us.
/03DocumentationArchitecture notes, runbooks, and onboarding docs for whoever comes next.
/04Handover & supportA working session with your team — then we stay reachable after launch.