Data Engineer

Akshit Gangwar

Data Engineer

+91-807******* *****************@*****.*** linkedin.com/in/akshitgangwar Noida, India Summary

Data Engineer with 3+ years building and optimizing ETL/ELT pipelines on Azure and AWS. Cut PySpark runtimes by 30%, reduced report refresh from 2 hours to 15 minutes, and migrated 30+ pipelines into a CI/CD-tested framework. Works day to day in PySpark, SQL, Delta Lake, dbt, and dimensional modeling on multi-terabyte datasets. Education

IIIT Bhubaneswar Jul 2019 – Jun 2023

Bachelor of Technology (B.Tech) in Information Technology Professional Experience

MAQ Software

Data Engineer Sep 2025 – Present

• Cut PySpark job runtime 30% by tuning Databricks clusters and parallelizing high-volume workloads, improving daily SLA adherence.

• Streamed 2M+ Braze API events/day into Delta Lake with Spark Structured Streaming for downstream customer analyt- ics.

• Architected 20+ Azure Data Factory pipelines orchestrating 50+ Databricks notebooks over multi-terabyte Delta Lake and Synapse tables.

• Migrated 30+ legacy PySpark pipelines to a Git-versioned, CI/CD-deployed Databricks framework on Azure DevOps, adding automated data-quality checks.

• Designed 15+ star-schema dimensional models on Delta Lake and Synapse for analytics and reporting workloads.

• Implemented RBAC and PII encryption across ~70% of production pipelines to meet internal security and audit reviews. LUMIQ (Crisp Analytics)

Data Analyst Jan 2023 – Sep 2025

• Reduced report refresh time from 2 hours to 15 minutes by re-architecting Python/PySpark ETL on AWS Glue with scheduled workflows.

• Developed dbt models with source and data-quality tests, validating data at ingestion before it reached reporting layers.

• Delivered Power BI dashboards with advanced DAX (MoM, YTD, variance) used by 500+ users, reducing recurring ad-hoc reporting requests.

• Standardized KPI definitions across teams using multi-source SQL on Redshift and Athena.

• Presented executive Power BI dashboards to leadership for use in planning reviews. Technical Skills

• Programming: Python (Pandas, PySpark), SQL (Joins, CTEs, Window Functions, SparkSQL), Scala

• Data Engineering: ETL/ELT Pipelines, dbt, Pipeline Migration, Star Schema, Dimensional Modeling, Data Warehousing, Data Quality, Delta Lake, Apache Iceberg, Lakehouse Architecture

• Streaming: Spark Structured Streaming

• Azure: Azure Databricks, Synapse Analytics, ADF, ADLS Gen2, Unity Catalog

• AWS: Redshift, Glue, EMR, S3, Athena, Lambda

• Orchestration & DevOps: Apache Airflow, Azure DevOps, Git, CI/CD Pipelines, Agile/Scrum

• BI & Visualization: Power BI (DAX, RLS, Power Query), Tableau, Amazon QuickSight, Excel

• Databases & Warehouses: Snowflake, BigQuery, NoSQL Projects

AI Job-Application Agent Python, LLM APIs (Cerebras/Groq/Gemini), Prompt Engineering, Playwright

• Built an autonomous multi-stage pipeline that scrapes 12 job sources, scores each role against a resume with LLM-based exact-keyword ATS matching, and generates per-job tailored resumes under prompt guardrails that prevent fabrication.

• Engineered a multi-provider LLM fallback chain with quota and empty-response handling to run reliably across free-tier rate limits.

Operational Efficiency Insights Power BI, Azure Data Factory, Databricks

• Created Delta Lake monitoring dashboards that surfaced pipeline bottlenecks and cut turnaround time 20%; configured trigger-scheduled ADF pipelines that improved reporting efficiency. Sales and Revenue Analysis Dashboard Power BI, SQL, Python, AWS Redshift

• Modeled multi-domain data into a Star Schema dashboard for regional revenue tracking and forecasting, with Python validation scripts that removed cross-report discrepancies. Certifications

• Microsoft Certified: Fabric Data Engineer Associate (2026)

• Microsoft Certified: AI Agent Builder Associate (2026)

• Microsoft Certified: Fabric Analytics Engineer Associate (2024)

• AWS Certified Developer – Associate (2024)

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