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Shreya Ghatnatti

Experienced Data Engineer specialising in ETL processes, automation pipelines, and proficient in SQL, Python, Data Analytics and BI tools (PowerBI and Tableau). Strong understanding of eCommerce intricacies, leveraging technical expertise and strategic insights to optimise data workflows for informed decision-making.

  • Role

    Senior Data Engineer

  • Years of Experience

    6 years

Skillsets

  • ETL/ELT pipelines
  • TeamCity
  • SQL Server
  • Shell Script
  • PySpark
  • Jira
  • Jenkins
  • IBM DB2
  • Hive
  • Hadoop
  • Git
  • Python
  • Data Warehousing
  • Azure DataBricks
  • Azure Data Lake Storage
  • Azure Data Factory
  • Apache Spark
  • Agile
  • MySQL
  • Azure
  • SQL

Professional Summary

6Years
  • May, 2024 - Present1 yr 9 months

    Senior Data Engineer

    ALTIMETRIK
  • Feb, 2021 - May, 20243 yr 3 months

    Senior Data Scientist

    ADA
  • Oct, 2018 - Dec, 20191 yr 2 months

    Product Specialist

    BYJUs

Applications & Tools Known

  • icon-tool

    Excel

  • icon-tool

    MySQL

  • icon-tool

    Azure

  • icon-tool

    Databricks

  • icon-tool

    Tableau

  • icon-tool

    PowerBI

  • icon-tool

    Apache Airflow

Work History

6Years

Senior Data Engineer

ALTIMETRIK
May, 2024 - Present1 yr 9 months
    Built and maintained 20+ production-grade data pipelines using Azure Data Factory and SQL, enabling real-time ingestion of server and workstation data for vulnerability analytics. Leveraged Databricks to process large-scale datasets, reducing pipeline execution time by 40% and increasing data throughput efficiency. Consolidated multiple structured sources into a unified Azure Data Lake schema, improving data accuracy and reducing reporting discrepancies by 30%. Implemented logic-based scheduling and data quality checks, ensuring 100% SLA adherence and delivery of analytics-ready data across teams. Facilitated cross-functional collaboration with product and engineering teams to align pipelines with evolving business logic, accelerating data-driven decisions by 15%. Standardized pipeline architecture and reusable components, resulting in a 20% boost in engineering efficiency and system maintainability.

Senior Data Scientist

ADA
Feb, 2021 - May, 20243 yr 3 months
    Designed and managed 40+ scalable pipelines using Apache Spark and Azure Data Lake Storage, powering month-end ledger processing across AP, AR, and Inventory. Unified data from multiple structured systems into a centralized cloud repository, improving accessibility and report generation times. Led full-scale migration from on-prem to Azure cloud, reducing retrieval latency by 45% and optimizing cost and performance. Cut month-end closure time from 710 days to just 12 hours (CD-1), and reduced compute costs by 25% through refined pipeline orchestration. Developed a Data Veracity Framework to validate schema and row-level consistency across ingestion layers, improving data trust by 30% and supporting audit readiness.

Product Specialist

BYJUs
Oct, 2018 - Dec, 20191 yr 2 months
    Analyzed user behavior patterns and feedback data to deliver insights that shaped product improvements and informed future feature prioritization. Collaborated with data, product, and engineering teams to bridge gaps between user needs and technical implementation, ensuring alignment between product outcomes and market feedback.

Achievements

  • Orchestrated end-to-end month-end closure (MEC) of Finance Ledgers
  • Spearheaded implementation of automation workflows
  • Achieved remarkable reduction in TAT for book closure
  • Built around 40 automation data pipelines using SparkSQL
  • Pioneered the implementation of Data Veracity checks
  • Provided on-call support every month-end
  • Consistently met and exceeded SLA for years

Education

  • PG Diploma in Data Science

    Manipal (2021)
  • Bachelor of Engineering, Electronics & Instrumentation

    BIET (2018)

Certifications

  • Databricks certified associate data engineer