Data Engineering • Data Analytics
Data Integration • Data Quality • Data Governance • Lakehouse • Qlik + Talend
I build end-to-end data solutions with one non-negotiable principle:
Pinned: data-portfolio • qliktalend_demos • qlik • (anchor repo in progress)
What I ship
- Integration patterns (APIs, orchestration, incremental loads)
- Reliability by default (idempotency, retries, error handling)
- Data Quality gates (profiling, rules, exceptions, monitoring)
- Governance-by-design (security mindset, lineage-ready structures)
- Lakehouse patterns (bronze/silver/gold)
What I ship
- Qlik semantic/KPI layers and reusable modeling patterns
- Security rules (row-level access patterns)
- Storytelling apps for decision-makers
High-signal repos designed as 1 demo = 1 repo (architecture + setup + results):
de-link-analysis-demo— entity resolution + relationship graph (public-sector style)de-data-quality-gates— profiling, rule severity, exceptions, reportingde-lakehouse-medallion— bronze/silver/gold + incremental loads
- Context (problem + constraints)
- Architecture (diagram + key decisions)
- Data (synthetic dataset + dictionary)
- Run it (reproducible setup, local and/or docker)
- Results (screenshots/outputs + takeaways)
- Trade-offs (limitations + what I’d change in production)
- LinkedIn: https://www.linkedin.com/in/wmnascimento
- Email: w4shington.mn@gmail.com