Data Engineer - Snowflake ELT, dbt, Python, SQL

GUNTAKA SUSHMITHA REDDY

Data Engineer Snowflake · ELT Pipelines · dbt · Python · SQL · API Integrations · Boomi

***********************@*****.*** +1-216-***-**** United States

PROFESSIONAL SUMMARY

Detail-oriented Data Engineer with 3+ years of hands-on experience owning and maintaining ELT pipelines, Snowflake data warehouse environments, and custom Python data applications that power reliable internal analytics and reporting. Strong proficiency in SQL and data modeling for analytical workloads with practical experience designing, building, and documenting new data models and transformations as business needs evolve. Experienced diagnosing and resolving pipeline failures, data quality issues, and performance bottlenecks with a methodical, root-cause-focused troubleshooting approach. Skilled in API integrations using Python and REST-based data sources, ELT automation tools including dbt and Airflow, and version control with GitHub. Familiar with enterprise integration platforms and iPaaS tooling, and experienced collaborating closely with BI and analytics teams as a technical data partner to scope and deliver new data integration projects.

TECHNICAL SKILLS

SQL & Data Modeling: Advanced SQL (CTEs, window functions, subqueries), analytical data modeling, schema design, star/snowflake schemas, performance optimization

Cloud Data Warehouse: Snowflake (primary) — data model ownership, table design, query optimization, warehousing concepts, data availability & consistency

ELT / ETL Pipeline Tools: dbt (Data Build Tool), Apache Airflow, AWS Glue, Alteryx, Matillion, Airbyte — pipeline design, transformation workflows, troubleshooting

Python & Scripting: Python (Pandas, NumPy, scikit-learn) — data processing, scripting, custom application maintenance, automation workflows

API & Integration Tools: REST API integrations, Python API scripting, Boomi (iPaaS/enterprise integration platform), Salesforce connector workflows

Version Control: GitHub — branching, pull requests, code review, version-controlled pipeline and transformation code

BI & Visualization: Tableau, Power BI, Looker — partnering with analytics teams, dashboard development, operational reporting

Databases & Platforms: Snowflake, PostgreSQL, Oracle EBS (familiarity), AWS (S3, Glue, EC2), Azure (Blob Storage, SQL Database), Databricks

Data Quality & Governance: Data validation frameworks, pipeline reliability monitoring, data consistency checks, documentation of systems and processes

Collaboration Tools: Salesforce, Microsoft Excel (pivot tables, macros), Agile/Scrum, stakeholder communication, institutional knowledge documentation

WORK EXPERIENCE

Wiz — United States Data Engineer Jul 2024 – Present

Primary technical resource for ELT pipelines, Snowflake data warehouse, and Python data applications supporting internal analytics and reporting

Owned day-to-day operation, maintenance, and enhancement of ELT pipelines and Snowflake data warehouse, ensuring data reliability, consistency, and availability for downstream analytics and reporting consumers across the organization.

Diagnosed and resolved pipeline failures, data quality issues, and performance bottlenecks using a methodical root-cause troubleshooting approach — digging into unfamiliar systems to identify and fix issues before they impacted stakeholder reporting.

Designed, built, and documented new data models and transformations in Snowflake as analytical needs evolved, maintaining clear institutional documentation of systems, processes, and design decisions for the team.

Improved existing ELT processes using dbt transformation tool to convert raw security telemetry data into clean, validated, schema-enforced formats — making data reliably available for downstream BI and analytics team consumers.

Developed and maintained scalable data pipelines using Apache Airflow orchestration tool to extract security event logs from AWS and Azure REST API endpoints, ensuring consistent, timely data ingestion into the Snowflake warehouse.

Built and maintained custom Python data processing applications for internal data workflows, contributing scripting automation and pipeline support code maintained in GitHub for version control and team collaboration.

Supported and extended API integration workflows using Python scripts connecting to REST-based cloud security data sources, processing structured and semi-structured API payloads into Snowflake-ready formats.

Implemented data quality checks and automated monitoring using Databricks tool for critical security pipeline data, ensuring accuracy and reliability of all analytical outputs consumed by program stakeholders.

Collaborated with internal analytics and BI stakeholders to scope and deliver new data integration projects, translating reporting requirements into concrete data model and pipeline designs using Snowflake and dbt.

Contributed to the evaluation of modern ELT tooling options including Matillion and Airbyte as potential improvements to the current pipeline architecture, documenting findings and trade-off analyses for team review.

Created complex analytical SQL queries in PostgreSQL and Snowflake, generating detailed governance and compliance reports on cloud resource configurations supporting internal audit and stakeholder review cycles.

Built automated Power BI reports and Tableau dashboards as a technical data partner for the analytics team, delivering reliable, well-structured data outputs that enabled accurate self-serve reporting.

Tools & Technologies: Snowflake, dbt, Apache Airflow, AWS Glue, Python, SQL, PostgreSQL, Databricks, REST APIs, GitHub, Tableau, Power BI, Looker, AWS, Azure, Alteryx

Pfizer — United States Data Engineer Jun 2022 – Nov 2023

ELT pipeline development, Snowflake data warehouse ownership, and Python automation supporting pharmaceutical R&D and commercial analytics

Owned and maintained ELT data pipelines and Snowflake data warehouse tables supporting R&D, supply chain, and commercial analytics teams — ensuring data reliability, consistency, and availability for downstream reporting consumers.

Designed and built comprehensive SQL data models in Snowflake to track drug development KPIs, patient enrollment statistics, and supply chain performance indicators — documenting data models and transformation logic for institutional knowledge.

Diagnosed and resolved data quality issues and pipeline performance bottlenecks in SQL-based extraction and transformation workflows, applying systematic root-cause analysis to restore data reliability for regulatory and business reporting.

Implemented automated ELT data extraction and transformation workflows using Python scripting and SQL automation tools, eliminating 15+ hours of weekly manual processing and improving pipeline reliability for routine business reporting.

Extended API integration workflows using Python scripts to connect Salesforce CRM REST API data into Snowflake, enabling marketing analytics teams to access up-to-date customer engagement data without manual exports.

Maintained and contributed to custom Python data processing applications used by the analytics team for pharmaceutical data workflows, managing code changes and versioning through GitHub for collaborative team development.

Designed data validation processes using SQL and Alteryx tool to ensure the accuracy of regulatory submission data, enforcing data consistency standards and protecting pipeline reliability for compliance reporting workloads.

Collaborated closely with BI and analytics teams as a technical data partner to scope and deliver new data integration projects, translating reporting and modeling requirements into Snowflake data model designs and pipeline implementations.

Managed and queried large-scale datasets in Snowflake across R&D and supply chain workloads, optimizing query performance and warehouse configuration to maintain availability SLAs for downstream consumer teams.

Documented data pipeline systems, transformation processes, and modeling decisions to build institutional knowledge, maintaining clear process documentation for team onboarding and system maintenance continuity.

Built predictive demand forecasting models using Python's scikit-learn library for supply chain teams, delivering forward-looking intelligence packaged as structured Snowflake datasets consumable by downstream BI reporting workflows.

Tools & Technologies: Snowflake, SQL, Python (Pandas, NumPy, scikit-learn), Alteryx, AWS Glue, Tableau, Power BI, PostgreSQL, Salesforce (REST API), GitHub, R, Microsoft Excel

EDUCATION

Master of Science — Information Systems Expected Jul 2025

Indiana Institute of Technology

Relevant Coursework: Data Engineering, Database Management Systems, Data Warehousing Concepts, Statistical Modeling, Information Systems, Python for Data Science, Cloud Computing

KEY ACHIEVEMENTS

Eliminated 15+ hours of weekly manual data processing at Pfizer by building automated Python and SQL ELT pipelines, freeing the analytics team to focus on higher-value reporting and modeling work.

Owned end-to-end Snowflake data warehouse at both Wiz and Pfizer, designing and maintaining data models consumed by multiple internal analytics and BI teams across two organizations.

Extended REST API integration workflows using Python at Pfizer to bring Salesforce CRM data directly into Snowflake, enabling marketing analytics to operate from a single reliable data source.

Contributed to ELT tooling evaluation at Wiz, researching Matillion and Airbyte as architectural improvement candidates and producing documented trade-off analyses for engineering and data leadership.

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