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Pooja Sankararaman

Pooja Sankararaman

Senior Data Operations Engineer | SQL · Python · ETL & Workflow Automation · Robotics/Warehouse Operations · Power BI

Talent
GrotonMember since August 18, 2026
SQLPythondbtREST APIsDatabricks notebooksGitHub ActionsCI/CDGreat ExpectationsAzure Data FactoryAWS S3Power BITableau DashboardsWorkflow AutomationData ClassificationJiraMySQLscikit-learn
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SQLPythondbtREST APIsDatabricks notebooks

About

Data Operations Engineer with 6+ years building SQL/Python-based ETL pipelines, workflow automation, and self-service Power BI reporting, including 3+ years embedded with a large-scale autonomous robotics deployment (Walmart Advanced Systems & Robotics) in a warehouse/fulfillment operations environment. Partners directly with robotics operations, engineering, and business stakeholders to turn fleet and operational data into KPI dashboards tracking uptime, throughput, and capacity, and to automate manual reporting into scalable, self-service datasets. Builds automated data quality and CI/CD workflows (Python, dbt, GitHub Actions, Great Expectations) across cloud platforms (AWS S3/Glue/Lambda, Azure Data Factory/Synapse/Databricks) to keep operational data trusted and accessible.

IIBA-certified in business analysis, Databricks Data Engineer Associate; M.S. in Business Analytics.

Experience

Data Engineer at Skulicity (2025-07 – Present)

  • Built automated data workflows and 150+ documented validation rules (Python, Great Expectations, SQL/dbt) to keep operational data accurate and self-service ready across teams
  • Built and optimized SQL/dbt ETL transformation logic within Databricks notebooks, improving query performance 30% on large operational data sets
  • Automated integration across Azure and AWS (S3, Glue, Lambda, Data Lake) via REST APIs and CI/CD (GitHub Actions), consolidating multi-source data into a single reporting layer and driving data accuracy to 99.5%

Data Engineer at Walmart Advanced Systems & Robotics (2022-10 – 2025-07)

  • Embedded with robotics operations and engineering teams to translate operational needs into automated Power BI dashboards tracking fleet uptime, throughput, and capacity across 15+ warehouse automation systems
  • Built and governed a tiered data classification framework (medallion architecture) so operations, engineering, and analytics teams could self-serve consistent, trusted operational data
  • Led a Python-based automated test and validation strategy (150+ checks) to catch data issues before they reached reporting, and improved dashboard/query performance 15% through SQL optimization
  • Partnered with engineering and operations through Agile ceremonies and Jira to scope, document, and prioritize a 20+ item backlog of continuous-improvement work based on business impact

Data Analyst at Innodatics (2021-04 – 2021-10)

  • Defined success metrics and built predictive models (Python, scikit-learn) to structure ambiguous risk data into clear customer segments, reducing attrition 10% and bad debt exposure 8%
  • Built self-service Tableau dashboards and MySQL schemas for stakeholders, automating manual reporting and cutting report turnaround time 30%

Data Analyst, Strategic Marketing at Bayer Pharmaceuticals (2018-08 – 2019-02)

  • Gathered requirements from marketing and product stakeholders to deliver dashboards and campaign/ROI analysis across a cardiology product portfolio, informing go-to-market and spend decisions on 10+ campaigns

Data Analyst, Global Marketing at B. Braun Medical (2017-01 – 2017-12)

Data Analyst at kaputt.de GmbH & Pyrexx (2017-01 – 2018-12)

Solvers Relation Manager at Hypios CI (2016-01 – 2017-12)

Education

M.S. in Business Analytics – Southern New Hampshire University (2021)

M.S. in Management; M.S. Innovation, Strategy & Entrepreneurship – Grenoble École de Management (2018)

B.Tech. in Biotechnology – SRM Institute of Science and Technology (2015)

Skills

Senior Data Operations EngineerSQLPythonETL & Workflow AutomationRobotics/Warehouse OperationsPower BI

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