Hemanth Pendam

Data Platform Engineer with five years of hands-on experience owning production pipelines from ingestion through transformation and delivery. Comfortable across the modern data stack, including Airflow and Prefect for orchestration, dbt for modeling and testing, Snowflake and Databricks for warehousing, Kafka and Spark Structured Streaming for real-time work, and Great Expectations for data quality. Writes clean, documented code, takes pipeline reliability seriously, and works effectively with analytics engineers, data scientists, and ML teams.

Has shipped dimensional models, streaming pipelines, and SLA alerting systems that teams rely on.

Data Platform Engineer - Lead IT Corporation - Springfield, IL

(2023-09)

Owns production pipelines from ingestion through transformation and delivery using the modern data stack.

• Built and maintained ETL/ELT pipelines with Airflow, pulling data from databases, APIs, event streams, and SaaS sources into Snowflake
• Developed dbt models across staging, intermediate, and mart layers using dimensional modeling and OBT patterns
• Implemented dbt tests, freshness checks, and documentation relied on by downstream analysts, maintaining clean data lineage across 15+ source systems
• Administered the Snowflake environment day to day by tuning clustering keys, right-sizing warehouses, tracking credit consumption, and optimizing slow queries
• Reduced query runtimes from minutes to seconds on critical tables and lowered monthly compute spend by 38%
• Built real-time streaming pipelines with Kafka and Spark Structured Streaming, reducing latency from four-hour batch windows to under twenty minutes
• Implemented Great Expectations checks and SLA alerting to surface failures immediately, and authored runbooks for team on-call diagnostics
• Collaborated with analytics engineers, data scientists, and ML engineers to translate requirements into pipeline specifications and structure datasets for BI consumption
• Authored technical documentation for pipeline architecture, data dictionaries, and on-call procedures used for team onboarding

Data Engineer - Lead IT Corporation - Springfield, IL

(2023-01 - 2023-06)

Developed ETL/ELT pipelines and data quality frameworks using Python and cloud-based data tools.

• Developed dbt models and Airflow DAGs for ETL/ELT pipelines on Snowflake and BigQuery, including dimensional modeling and incremental models
• Built Great Expectations quality checks and alerting for SLA violations
• Implemented Kafka event-driven ingestion and Spark Structured Streaming for real-time processing
• Applied Python scripting to orchestration and data processing, reducing pipeline failures by 45%

Data Engineer - Tech Mahindra - India

(2021-01 - 2022-08)

Managed end-to-end data infrastructure and transformation layers within a cloud environment.

• Owned ETL/ELT pipelines and dbt transformation layers on Snowflake and Databricks with Airflow orchestration
• Implemented Kafka streaming and Spark Structured Streaming for data processing
• Applied Great Expectations for data quality and dimensional modeling for warehouse design
• Partnered with analytics engineers and data scientists to translate business requirements into technical pipeline designs
• Authored technical documentation for architecture and on-call runbooks, contributing to a 25% reduction in cloud costs

Masters - Data Analytics - University of Illinois Springfield (2024-05)

Bachelor - Information Technology - Sreenidhi Institute of Science and Technology