Senior Data Engineer - Linux Data Warehouse Specialist

kyanam Dinesh — Senior Data Engineer

913-***-**** **************@*****.***

PROFESSIONAL SUMMARY:

Leveraging around 5 years of comprehensive experience in the IT industry, specializing as a Data Warehouse Engineer with a strong emphasis on Linux-based data solutions.

Proven expertise in implementing, configuring, and managing robust Linux-based processes and infrastructure critical for high-performance data warehousing.

Adept at identifying and implementing system and architecture improvements, focusing on optimizing data flows and ETL/database load/extract processes.

Extensive practical experience in Linux environment setup, including deep knowledge of Unix file systems, mount types, permissions, and standard command-line tools.

Highly proficient in Shell Scripting, utilizing it for enhancing various Linux-based toolsets, automating jobs, and streamlining complex data processing operations.

Skilled in Oracle development and administration, with practical working experience in relational databases, including optimizing queries and managing data structures.

Demonstrated working knowledge of Python for scripting, data manipulation, and automation tasks, contributing to efficient data engineering workflows.

Experienced with ETL tools, including Informatica, for designing and implementing scalable data ingestion and transformation pipelines.

Proficient in using orchestration tools, specifically Apache Airflow with Python, for scheduling, monitoring, and managing intricate data warehousing jobs.

Strong understanding of the Agile methodology, actively participating in sprint-based delivery and fostering continual process improvement in data engineering projects.

Passionate about automation, consistently seeking opportunities to enhance operational efficiency and reduce manual intervention in data warehouse environments.

Excellent written and oral communication skills, effectively collaborating with cross-functional teams and articulating complex technical concepts clearly.

WORK EXPERIENCE:

Senior Data Engineer @ Optum Eden Prairie, MN Aug 2024 – Present

Implemented, configured, and managed critical Linux-based processes and infrastructure to support scalable healthcare data warehousing operations.

Designed and deployed robust shell scripts to automate complex data extraction, transformation, and loading (ETL) routines for Oracle databases.

Enhanced various Linux-based toolsets, scripts, jobs, and processes to optimize data flows and improve system performance for large datasets.

Developed and maintained high-performance ETL pipelines, focusing on Oracle development and ensuring efficient database load and extract processes.

Administered and optimized Oracle database instances, including performance tuning and schema management for critical data warehouse applications.

Leveraged Python for developing custom data processing scripts and automating operational tasks within the Linux environment, reducing manual effort.

Ensured data integrity and security for sensitive healthcare information by implementing stringent access controls and encryption on Linux systems.

Identified and implemented system and architecture improvements, resulting in a 15% reduction in data processing time and enhanced reliability.

Managed Unix file systems, including configuring mount types, setting permissions, and utilizing standard tools and pipes for data manipulation.

Integrated data from diverse sources into the data warehouse, applying advanced SQL and PL/SQL for complex transformations and data quality checks.

Orchestrated batch workflows using Apache Airflow with Python, ensuring reliable scheduling, monitoring, and alerting for all data warehouse jobs.

Actively contributed to DevOps practices by automating build and deployment processes for data solutions in a continuous integration/continuous delivery pipeline.

Collaborated with cross-functional teams to define data requirements and translate them into efficient data warehouse designs and implementation plans.

Maintained comprehensive documentation for Linux system configurations, shell scripts, and Oracle database procedures to facilitate knowledge sharing.

Participated actively in Agile Scrum ceremonies, driving continuous improvement in data engineering practices and ensuring timely project delivery.

Technologies Used: Linux, Shell Scripting, Oracle, Python, Apache Airflow, SQL, PL/SQL, AWS (EC2, S3), GitHub, Jenkins

Data Engineer @ Wells Fargo San Francisco, CA Apr 2022 – Jun 2023

Established and managed Linux-based environments within Azure to host critical data warehousing components for banking and risk analytics.

Developed and implemented extensive shell scripts for automating data ingestion, validation, and transformation processes from various sources into Oracle.

Enhanced ETL/database load and extract processes, specifically focusing on optimizing data movement into and out of Oracle relational databases.

Designed and built robust data pipelines using Python and shell scripting to process transactional and customer data efficiently on Linux servers.

Managed and optimized Oracle databases, including schema design, query optimization, and performance tuning to support analytical requirements.

Implemented data integration solutions leveraging Unix file system knowledge to handle diverse data formats and ensure data quality and consistency.

Provided practical working experience with relational databases, ensuring data models and queries were optimized for performance and scalability on Oracle Exadata.

Migrated legacy on-premise data processes to cloud-based Linux environments on Azure, enhancing system reliability and reducing operational costs.

Utilized expertise in Unix file systems, including mount types, permissions, and standard tools, to secure and manage sensitive financial data.

Automated system monitoring and alerting for Linux-based data infrastructure using custom shell scripts, improving proactive issue resolution.

Contributed to the development of data warehousing solutions, ensuring efficient data flows and adherence to financial compliance requirements.

Collaborated with data architects to identify and implement system and architecture improvements within the Linux data processing ecosystem.

Implemented source code management for shell scripts and Python programs using GitHub, ensuring version control and collaborative development.

Performed thorough data validation, unit testing, and reconciliation checks on ETL processes to ensure the accuracy of financial data in the data warehouse.

Participated actively in Agile sprint planning, reviews, and retrospectives, contributing to iterative development and continuous improvement of data solutions.

Technologies Used: Linux, Shell Scripting, Oracle, Python, SQL, Azure (ADLS Gen2, Databricks), Unix, GitHub, Jenkins Junior Data Engineer @ Big Lots Columbus, OH Nov 2020 – Mar 2022

Supported and enhanced data pipelines for retail and merchandising analytics, focusing on robust ETL operations within an Oracle environment.

Developed and maintained ETL workflows using Informatica to ingest data from Oracle and diverse flat file sources into the data warehouse.

Performed complex data transformations using SQL and PL/SQL, ensuring data accuracy and consistency for reporting and analytics.

Built and maintained dimensional data models to support sales and inventory reporting, optimizing for query performance and data retrieval.

Optimized SQL queries to significantly improve reporting and batch processing performance, reducing execution times by up to 20%.

Implemented data validation and reconciliation checks to ensure high data accuracy and reliability across all retail data sets.

Supported reporting datasets consumed by downstream BI teams, ensuring timely and accurate data availability for business intelligence.

Managed version control for SQL scripts and Informatica mappings using GitHub, adhering to standard development and deployment processes.

Contributed to the automation of routine data tasks using basic shell scripts within a Linux environment, improving operational efficiency.

Assisted in the setup and configuration of Linux-based tools used for data transfer and processing, gaining practical Unix experience.

Collaborated with senior engineers to troubleshoot and resolve data-related issues, ensuring minimal impact on business operations.

Gained practical working experience with relational databases, specifically Oracle, in a production data warehousing context.

Participated in the enhancement of ETL/database load and extract processes under guidance, contributing to process efficiency.

Maintained documentation for ETL processes and database schema changes, ensuring knowledge transfer and system maintainability.

Adhered to Agile methodologies in project execution, participating in team meetings and contributing to sprint goals. Technologies Used: Oracle, Informatica, SQL, PL/SQL, Linux, Shell Scripting, GitHub TECHNICAL SKILLS:

Programming Languages: Python, SQL, PL/SQL

Scripting & Operating Systems: Shell Scripting, Unix, Linux, CentOS, Ubuntu

Databases: Oracle, Oracle Exadata, MySQL, PostgreSQL, SQL Server

ETL & Data Warehousing: Informatica, AWS Glue, Azure Data Factory, Data Modeling, Dimensional Modeling, OLAP, Synapse Analytics

Orchestration & Automation: Apache Airflow, AWS Step Functions, Jenkins

Cloud Platforms: AWS (EC2, S3, RDS), Azure (ADLS Gen2, Databricks)

Version Control & Methodologies: Git, GitHub, Agile (Scrum), DevOps EDUCATION:

Master of Science in Computer Science @ University of Central Missouri

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