Data Engineer Big

Veerendra Dheeraj Relangi

Data Engineer

***********@*****.*** 339-***-**** San Jose, CA

PROFESSIONAL SUMMARY

Detail-oriented and adaptable Data Engineer with 4+ years of experience designing, building, and maintaining robust data pipelines and analytics solutions in fast-paced, collaborative environments. Highly proficient in SQL and Python, with deep expertise in big data frameworks (Hadoop, Spark, Kafka), cloud platforms (AWS, Azure), and advanced data modeling, ETL processes, and data governance practices. Demonstrates strong problem-solving skills, an eye for detail, and a passion for transforming complex raw data into business value. TECHNICAL SKILLS

Programming: Python, SQL, PySpark, Scala

Big Data: Hadoop (HDFS, Hive), Apache Spark, Apache Kafka ETL & Orchestration: Apache Airflow, AWS Glue, Azure Data Factory, dbt Cloud Platforms: AWS (S3, Redshift, Lambda), Azure (Data Lake Storage, Databricks) Databases: Snowflake, AWS Redshift, PostgreSQL, MongoDB, Cassandra Streaming: Kafka Streams, Spark Streaming

Data Modeling: Star/Snowflake Schemas, Dimensional, OLAP/OLTP Data Quality & Governance: Great Expectations, Apache Atlas, Data Encryption Visualization: Power BI, Tableau

DevOps/CI/CD: Git, Jenkins, Docker, Terraform, GitHub Actions Security: RBAC, GDPR, Key Vault, Data Encryption

Monitoring: Prometheus, Grafana, ELK Stack (Elasticsearch, Logstash, Kibana) PROFESSIONAL EXPERIENCE

eBay – San Jose, CA

Data Engineer Aug 2023 – Present

Developed and maintained enterprise-grade data pipelines in SQL and Python ensuring reliable, efficient data flow between diverse source systems and cloud data warehouses (AWS Redshift, Snowflake).

Automated ETL/ELT workflows using Apache Airflow, optimizing pipeline scheduling and dependencies to support low-latency analytics.

Architected and deployed big data streaming solutions using Apache Kafka and Spark Streaming to deliver real-time datasets for business-critical dashboards.

Collaborated cross-functionally with data scientists and analysts to provide high-quality, model-ready data and enable seamless data-driven decision-making.

Designed robust, cost-effective data models (star/snowflake) to optimize storage, accelerating analytical workloads and reducing query response times.

Led migration of on-premise data workloads to AWS, ensuring secure, scalable, and highly available data infrastructure.

Built and maintained robust data validation frameworks (using Great Expectations) to protect data quality and integrity at each stage of the pipeline.

Proactively participated in architectural reviews, consistently proposing improvements that enhanced system scalability, resiliency, and performance.

Contributed to development and enforcement of company-wide data governance standards and best practices to ensure compliance and data consistency.

Enabled end-users with intuitive Power BI/Tableau dashboards, lowering time-to-insight and democratizing analytics.

Tata Consultancy Services (TCS) – Hyderabad, India Data Engineer Feb 2019 – Jul 2021

Built cloud-native batch and streaming data pipelines leveraging Hadoop, Spark, and Kafka for financial and retail datasets exceeding 2TB/day.

Designed intricate ETL processes with Python, SQL, and Airflow, automating data cleansing, aggregation, and transformation across multiple business domains.

Implemented data ingestion pipelines using Azure Data Factory and AWS Glue, ensuring seamless integration between disparate data sources and cloud storage (S3, Data Lake).

Modeled and maintained large-scale OLAP data marts in Snowflake and Redshift, supporting ad-hoc queries and complex reporting at scale.

Instituted end-to-end data quality checks, anomaly detection, and automated alerts to safeguard reliability of production analytics.

Partnered with analytics teams to enable feature engineering and rapid experiment design via shared, well- documented datasets.

Supported infrastructure-as-code (Terraform, Jenkins, GitHub Actions) for repeatable, compliant, and auditable deployments.

Drove implementation of real-time monitoring and logging (Prometheus, ELK Stack) to identify pipeline issues proactively and expedite troubleshooting.

Participated in review and refinement of data governance policy, ensuring compliance with GDPR and internal security procedures.

EDUCATION

Master’s in Computer Science – California State University, East Bay Bachelor’s in Computer Science – GITAM University, Visakhapatnam, AP

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