Skills: Excel, SQL, Python, R, Tableau, Power BI,
Looker, dbt, Airflow, Snowflake, BigQuery, Spark,
Pandas, NumPy, Statistics, Machine Learning, A/B
Testing, Git, Jira, Agile, Scrum, Kanban.

Core stack:
• SQL (3 yrs) — window functions, CTEs, query tuning
• Power BI + DAX (2 yrs) — 4 dashboards used weekly by
  6 regional sales managers
• Python (Pandas) — ETL and ad-hoc analysis
• dbt — 12 models; tests on every column that ships

- Improved conversion by 15%.

- Conversion from 2.1% to 2.4% (+15% relative) after
  instrumentation fix; verified on a 6-week A/B with
  ~120k sessions (p < 0.05).

- Built dashboards in Power BI for sales reporting.

- Built a 4-page Power BI dashboard used weekly by
  6 regional sales managers; public demo:
  bit.ly/you-sales-viz (demo data).

- Worked with clean data.

- Added dbt tests on 12 models (not_null, unique,
  referential); reconciled revenue between the app DB
  and the warehouse monthly; caught 3 silent data
  drops in 6 months before they hit exec reporting.

- Created weekly reports in Excel.

- Automated weekly reporting with a scheduled SQL job in
  Airflow + a Power BI refresh; cut manual effort from
  6 h/wk to ~20 min/wk and eliminated ~90% of
  copy-paste errors.

Objective:
To work in a challenging role as a Data Analyst where
I can leverage my analytical skills.

Data Analyst · 3 yrs
SQL · Power BI · Python (Pandas) · dbt
Reduced weekly reporting from 6 h to 20 min for a
40-person sales org; cut stale-data incidents by 70%.

Data Analyst — Brightpath Pvt Ltd (2022-2024)
- Created weekly reports in Excel and Power BI.
- Wrote SQL queries for ad-hoc analysis.
- Worked with the marketing team.
- Built dashboards for management.

Projects
- Titanic survival analysis (Kaggle).
- Sales dashboard with Excel.

Data Analyst — Brightpath Pvt Ltd (2022-2024)
- Owned weekly reporting for a 40-person sales org; cut
  manual effort from 6 h/wk to ~20 min/wk by rebuilding
  the pipeline in Power BI + scheduled SQL (dbt + Airflow).
- Built a 4-page Power BI dashboard used weekly by 6
  regional sales managers; public demo:
  bit.ly/you-sales-viz
- Rewrote a 90-line daily report as a single CTE; runtime
  from 14 min to 40 s (measured over 1 week).
- Added dbt tests on 12 models; reconciled revenue
  monthly; caught 3 silent data drops before they hit
  exec reporting.
- Partnered with marketing to instrument 12 campaign
  events; attribution coverage from 40% to 92%.
- Ran a 4-week A/B (~120k users) on the checkout page;
  +4.2% conversion, no increase in returns (guardrail).

Projects
- Churn analysis on a public SaaS dataset — segmented
  8k accounts, flagged 3 risk clusters, wrote a 1-page
  memo recommending an intervention (public notebook).

Content (1-6):
☐ Tools list is 3-5 items with depth.
☐ SQL technique named (CTEs, window functions, tuning).
☐ Business impact on 2+ bullets.
☐ Metrics paired with a baseline.
☐ One domain named (fintech, SaaS, retail, health).
☐ Every project has a "so what" / insight line.

Artefacts (7-11):
☐ One public dashboard link.
☐ No Kaggle tutorial as a primary project.
☐ One data quality line (dbt tests, reconciliation).
☐ One reproducible repo or notebook.
☐ One written artefact (memo, deck, write-up).

Tooling (12-15):
☐ One modern tool (dbt, Snowflake, BigQuery, Redshift).
☐ One automation line (Airflow, cron, scheduled SQL).
☐ One A/B or experimentation line.
☐ One "explained data to X" line.

Positioning (16-18):
☐ Opening line = role + stack + one impact number.
☐ Stakeholders named (who used the work).
☐ Decisions moved (what changed).
☐ No bullet copied from a JD.
☐ One page for 2-5 years of experience.
☐ Filename: Firstname-Lastname-DA-Resume.pdf