Data Engineer Analytics

Rohith Pasham Data Analytics Engineer

Columbus, Ohio ****************@*****.*** +1-614-***-**** LinkedIn SUMMARY

4+ years of experience in data engineering, big data processing, and ETL pipeline development, ensuring efficient data ingestion, transformation, and optimization.

Strong expertise in SQL & NoSQL databases (PostgreSQL, MS SQL Server, MongoDB), specializing in query performance tuning, indexing, and data integrity management.

Proficient in building real-time and batch data pipelines using Apache Kafka, Spark Streaming, and Flink, optimizing data flow for large-scale processing.

Hands-on experience in ETL workflow orchestration with Apache Airflow, AWS Glue, and dbt, enabling seamless automation and data transformation.

Deep understanding of data warehousing and cloud analytics using Snowflake, Google BigQuery, AWS Redshift, and Azure Synapse to support scalable analytics solutions.

Executed CI/CD pipelines for data workflows and monitoring system performance with Datadog, Prometheus, and AWS CloudWatch to enhance reliability.

Strong background in data governance, security, and compliance, implementing RBAC, encryption, and GDPR-compliant data solutions for enterprise environments.

Experienced in integrating data visualization tools like Tableau, Power BI, and Looker, optimizing analytics dashboards for business insights.

SKILLS

Data Analytics Tools: Power BI, Tableau, Jupyter Notebook, Google Data Studio, SQL Developer, Apache Superset Programming Languages: Python, R, SQL, T-SQL, SAS, PySpark Management Tools: JIRA, SharePoint, Confluence, Bitbucket, GitHub, Trello Databases: PostgreSQL, MS SQL Server, MySQL, Oracle, Teradata, Snowflake Big Data Technologies: Hadoop, HDFS, MapReduce, Hive, Pig, Spark, Google BigQuery, AWS Redshift Cloud Platforms & Services: AWS (S3, Redshift, Glue, Lambda, EC2, IAM), Azure (Synapse, Data Factory, Databricks), GCP

(BigQuery, Data Proc)

Data Engineering & ETL: ETL & ELT (Extract, Transform, Load), Apache Airflow, AWS Glue, Data Wrangling, Data Cleaning Streaming Technologies: Apache Kafka, Kafka Streams, Spark Streaming, AWS Kinesis Data Visualization & Reporting: Data Visualization, Dashboards & Reporting, KPI Analysis, Business Intelligence Analytics & Decision-Making: Risk & Decision Analysis, A/B Testing, Predictive Analytics, Data-Driven Decision Making Machine Learning & AI: Regression Analysis, Classification Modeling, Statistical Inference, Deep Learning Statistical Techniques & Libraries: ANOVA, Time Series Analysis, Pandas, NumPy, SciPy, TensorFlow, Scikit-Learn, PySpark Methodologies & SDLC: SDLC, Agile, Scrum, Waterfall, DevOps, CI/CD Modern Data Engineering Tools: Snowflake, Databricks, AWS Redshift, Google BigQuery, Azure Synapse Operating Systems: Windows, Mac, Linux

EXPERIENCE

ACL Digital, USA Data Engineer Jun 2024 – Present

Designed and deployed scalable machine learning pipelines using Scikit-learn, TensorFlow, and PySpark, enhancing predictive analytics and data-driven decision-making.

Developed and enhanced ETL pipelines using AWS Glue, Apache Airflow, Informatica PowerCenter, and dbt, improving data ingestion, transformation, and integration efficiency by 35%.

Processed and analyzed large-scale datasets leveraging Hadoop ecosystem tools like Hive, Pig, and Spark, extracting actionable insights to support data-driven strategies.

Enhanced data processing efficiency by 20% through performance tuning, model optimization, and hyperparameter adjustments, improving analytics accuracy.

Architected and deployed data warehousing solutions using Snowflake, Google BigQuery, and AWS Redshift, enhancing storage efficiency, query performance, and data accessibility by 40%.

Developed and managed SQL Server databases, creating stored procedures, user-defined functions, and automated workflows, streamlining daily data processing.

Engineered real-time data pipelines with Apache Kafka, facilitating low-latency streaming, event-driven processing, and seamless data integration.

Optimized data ingestion workflows in Hadoop, transforming Kafka stream data into structured formats to support business intelligence and analytics.

Applied and streamlined data visualization solutions using Tableau, Power BI, and Looker, integrating AWS S3, RDS, and Redshift, which improved real-time monitoring and reporting efficiency by 45%.

Implemented robust data security and compliance measures across AWS, Azure, and GCP, ensuring data integrity, backup, disaster recovery, and regulatory compliance.

CueTech Systems, India Data Engineer Mar 2019 – Aug 2022

Led cloud migration from on-premise to AWS and Azure, cutting operational costs by 30% and enhancing global data accessibility.

Developed 15+ interactive dashboards using Tableau & Power BI, improving KPI visibility by 40% and enhancing business performance tracking.

Optimized SQL database performance, restructuring schemas and queries to reduce latency by 50% and improve report generation by 35%.

Built automated ETL pipelines using AWS Glue, GCP Data Proc, and Azure Synapse, streamlining data integration and transformation across multiple sources.

Automated data workflows in Power BI, SQL Server, and Excel, reducing manual reporting efforts by 40% and increasing operational efficiency.

Conducted customer behavior analysis using SQL and Python, leading to a 10% increase in customer retention and satisfaction.

Streamlined logistics operations by analyzing large geospatial datasets with PostGIS, improving delivery efficiency by 25%.

Collaborated with cross-functional teams, participating in 30+ requirements-gathering sessions to ensure on-time, budget-friendly project execution.

EDUCATION

Master in Data Analytics Franklin University, Columbus, Ohio Bachelor in Electronics and Communications Engineering Jawaharlal Nehru Technical University, Hyderabad

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