Satish nagala

Key Responsibilities:

• Designed, developed, and maintained scalable ETL/ELT data pipelines using Snowflake, DBT, and Python, optimizing data ingestion and transformation for the automotive spare parts domain.
• Built and managed over 20+ automated pipelines, reducing manual data processing time by 60%, enabling faster business insights.
• Architected and implemented data warehousing solutions, facilitating seamless integration of multiple data sources and supporting data analytics across operations, logistics, and sales.
• Developed and maintained complex SQL queries, tables, views, and stored procedures, improving data accessibility and reducing report generation time by 35%.
• Led access management and role-based permissioning within Snowflake, ensuring compliance with internal data governance policies and enhancing platform security.
• Collaborated with cross-functional teams (BI analysts, operations, sales) to define data requirements, resulting in 20% faster deployment of analytical dashboards.
• Monitored and maintained production data pipelines to ensure 99.9% uptime and consistent data quality across all reporting layers.
• Standardized transformation logic using DBT models, improving code reusability and reducing onboarding time for new team members by 40%.
• Drove data-driven decision-making by ensuring timely delivery of clean, validated, and actionable data assets.

Key Responsibilities:

• Assisted in building and maintaining basic data pipelines using SQL and Python, supporting internal analytics and reporting teams.
• Supported senior data engineers in data extraction, cleaning, and transformation of structured and semi-structured datasets.
• Collected data from various sources, applied required transformations, and loaded it into database.
• Maintained and updated code repositories, ensuring version control and consistency across development environments.
• Participated in the development of data models and views under supervision to support dashboards and operational reporting.
• Helped document and organize datasets to make it easier for the team to understand where the data comes from and how it's structured.

Key Responsibilities:

• Tracked and analyzed daily production data using Microsoft Excel, including pivot tables and charts, to identify bottlenecks and generate shift-wise performance reports for management.
• Executed basic SQL queries to retrieve and analyze production metrics from internal databases, supporting weekly reports on efficiency and machine downtime.
• Partnered with process engineers to digitize production reporting templates, reducing manual errors and improving data consistency across departments.
• Participated in daily planning meetings and presented data-driven insights to enhance workflow efficiency and optimize shift resource allocation.