Ruthvi Lohar

I’m a Data Analyst with 2+ years of experience delivering high-quality data solutions across enterprise environments, supporting business-critical systems in consulting and delivery-center models. I focus on building reliable data foundations that stakeholders can trust, and I bring a client-focused mindset aligned to fast-paced delivery.

At Backer Labs Tech, I led data quality engineering and production support for large-scale enterprise data platforms. I designed, wrote, and optimized complex SQL (CTEs, window functions, performance tuning) to validate, reconcile, and audit high-volume datasets across relational and distributed environments.

I worked extensively with Azure Databricks and Spark to build, monitor, and optimize scalable data pipelines, ensuring data accuracy, completeness, and performance. I also authored technical documentation and trained junior engineers and analysts on data quality standards, SQL best practices, and support procedures.

I’m comfortable owning end-to-end lifecycle work—incident resolution, root cause analysis, and continuous process improvement. I developed data quality frameworks (validation rules, reconciliation checks, exception handling, automated monitoring), built operational dashboards (Power BI/Tableau), and automated validation and reporting with Python, SQL, and Spark to reduce manual effort and improve delivery timelines.