Scalable Data Pipelines & Analytics Dashboards

The assignment covers three tightly-linked streams of work. First, I need end-to-end data pipelines and ETL workflows that ingest, transform, and load data at scale so our analysts can tap into clean, well-modeled tables without delay. Second, the transformed data must surface in engaging, self-service dashboards—primarily built in Power BI, though I’m open to Looker or Tableau where it makes sense. Third, every dataset we touch has to pass strict quality checks and align with the company’s governance standards, so automated validation, lineage tracking, and clear data dictionaries are part of the scope.

You’ll work directly with me and our Analytics Center of Excellence, translating business questions into technical designs, collaborating with data scientists on modeling choices, and guiding business users toward greater data literacy along the way. I’m flexible on the underlying stack; if you prefer Spark, Kafka, Airflow, or a different orchestration layer, make the case—performance, reliability, and maintainability are the deciding factors.

Key deliverables
• Production-ready, modular data pipelines with deployment scripts
• A documented data quality and governance framework (tests, alerts, lineage)
• Interactive dashboards and reports connected to the new model
• Clear runbooks and hand-off documentation so future enhancements are seamless

I’ll consider the project complete once pipelines refresh reliably on schedule, data assets meet agreed-upon quality thresholds, and end users can answer their core reporting questions through the published dashboards without manual intervention.