Ankit R.

I help growing companies turn messy operational data into reliable, analytics-ready infrastructure — and turn that data into insights teams actually use to make decisions. Over 5+ years, I've worked across the full data lifecycle for a logistics/SaaS company: building production pipelines, modeling data warehouses, optimizing databases, and delivering the reporting and analysis that came out the other end. Data Engineering Production ETL/ELT pipelines (batch and real-time/CDC) Data warehouse design & modeling (star/snowflake schema, SCD) Database optimization — query tuning, indexing, materialized views Orchestration (Airflow) and transformation (dbt) Automating manual/Excel-based reporting workflows Data Analysis & BI Exploratory analysis and ad hoc SQL reporting KPI frameworks and business metrics design Dashboard build-outs (Power BI, Apache Superset) Data cleaning, validation, and reconciliation Translating raw data into decisions — not just charts Tools I work in: Python, SQL, PostgreSQL, MySQL/MariaDB, MongoDB, BigQuery, ClickHouse, Databricks, PySpark, Apache Airflow, Apache NiFi, Debezium (CDC), dbt, Kafka, Power BI, Apache Superset. Where I add the most value: companies (10–500 employees) in SaaS, logistics, e-commerce, or fintech — whether you need someone to build the pipeline from scratch, fix a database that's buckling under real usage, or just make sense of the data you already have. Comfortable owning a project end-to-end, or plugging into a specific piece (a query, a dashboard, a pipeline fix) — happy to scope to what you actually need. Let's talk about what's slowing your data down.