Anudeep Rao Daggu
Dallas,Texas
Summary
Data Engineer with 4 years of experience delivering scalable data solutions across healthcare and business domains. Skilled in building ETL/ELT pipelines, data modeling, and cloud-native platforms (AWS, Azure, GCP). Proven ability to partner with data science and analytics teams to operationalize predictive models and deliver actionable insights. Experienced in improving pipeline performance, standardizing data practices, and mentoring peers to ensure stability, quality, and security in data platforms. Results-focused data professional equipped for impactful contributions. Expertise in designing, building, and optimizing complex data pipelines and ETL processes. Strong in SQL, Python, and cloud platforms, ensuring seamless data integration and robust data solutions. Known for excelling in collaborative environments, adapting swiftly to evolving needs, and driving team success.
Overview
5
5
years of professional experience
1
1
Certification
Work History
Data Engineer
Johnson & Johnson
08.2024 - Current
- Built and optimized large-scale ETL/ELT pipelines using Snowflake, Airflow, and Kafka, reducing fraud detection latency by 22% and improving reporting accuracy.
- Partnered with data scientists to integrate predictive models into production workflows, enabling faster decision-making for executives.
- Designed a semantic data layer across 15+ domains, reducing ad hoc query load by 40% and accelerating dashboard performance.
- Enforced data quality, access control, and monitoring standards, cutting unauthorized access incidents by 40% and ensuring compliance.
- Standardized data modeling practices across teams, reducing production defects by 15% and improving downstream reporting reliability.
- Directed a 5-member team in pipeline modernization efforts, delivering resilient, self-healing data workflows with Kubernetes-based automation.
- Environment: AWS, Azure, Snowflake, Airflow, Python, SQL, Kafka, Jenkins, Kubernetes, Power BI
Data Engineer
Cardinal Health
01.2021 - 07.2023
- Migrated legacy ETL systems to AWS Glue and Snowflake, reducing processing time by 30% and eliminating SLA breaches.
- Developed 50+ reusable dbt models to standardize analytics, increasing adoption of self-service reporting and reducing backlog requests.
- Reengineered Spark-based pipelines to optimize large-scale data processing, improving dashboard performance by 60%.
- Built real-time streaming pipelines with Kafka and GCP Pub/Sub, enabling instant visibility for 5 business units.
- Automated workflows using Airflow DAGs, cutting manual intervention by 80% and improving system reliability.
- Mentored junior engineers on DevOps and IaC practices, reducing incident tickets by 15% and improving onboarding efficiency by 20%.
- Environment: AWS, GCP, Snowflake, PySpark, Airflow, dbt, Terraform, BigQuery
- Designed and implemented ETL processes for data integration across multiple systems.
- Developed data pipelines using Apache Spark to enhance data processing efficiency.
- Collaborated with cross-functional teams to define data requirements and ensure alignment with business objectives.
- Optimized SQL queries to improve database performance and reduce processing time.
- Conducted root cause analysis on data discrepancies, providing actionable insights for resolution.
Education
Master of Science - Cybersecurity Operations
Webster University
San Antonio, Tx05.2025
Bachelor of Science - Electronics and Communication Engineering
Hyderabad Institute of Technology And Management
Hyderabad, India.07.2022
Skills
- Languages: Python (OOP, NumPy, Pandas), SQL, Shell Scripting, Excel
- Big Data & Frameworks: Apache Spark, PySpark, Apache Kafka, Apache Flink, Delta Lake, Apache Iceberg
- Workflow & Orchestration: Apache Airflow, dbt, Oozie, CI/CD Pipelines
- DevOps & Tools: Git, Jenkins, Docker, Kubernetes, Terraform
- Cloud Platforms: AWS (Glue, Lambda, EC2, Redshift), Azure (Data Factory, Synapse), GCP (BigQuery, Dataflow, Pub/Sub, Cloud Composer), Databricks
- Databases: Snowflake, MS SQL Server, MySQL, Oracle, DB2, Teradata, Netezza, MongoDB, HBase, Cassandra, MariaDB
- Reporting & Others: Power BI, Crystal Reports XI, SSRS, Cognos, MS Office Suite
- Operating Systems: Windows, Linux, UNIX, Mac
- Data warehousing
- Data modeling
- Data pipeline design
Certification
Infosys Data Science with Spark Jul 2023.
Timeline
Data Engineer
Johnson & Johnson
08.2024 - Current
Data Engineer
Cardinal Health
01.2021 - 07.2023
Master of Science - Cybersecurity Operations
Webster University
Bachelor of Science - Electronics and Communication Engineering
Hyderabad Institute of Technology And Management
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