Senior Data Engineer with Linux & ETL Expertise

Rishitha Chilukuri — Senior Data Engineer

737-***-**** *******************@*****.***

PROFESSIONAL SUMMARY:

Highly accomplished Senior Data Engineer with 5 years of progressive experience in data warehousing and robust Linux- based infrastructure management.

Expertly implemented, configured, and managed complex Linux-based processes for high-performance data warehousing solutions, ensuring operational efficiency.

Proactively identified and implemented significant system and architecture improvements, enhancing overall data platform stability and scalability.

Proficiently enhanced various Linux-based toolsets, shell scripts, automated jobs, and critical data processes to optimize data flows.

Specialized in enhancing ETL and database load/extract processes, with a strong focus on Oracle development and ensuring data integrity.

Possesses practical working experience in setting up Linux environments and developing intricate shell scripting solutions for automation.

Demonstrated in-depth knowledge of Unix file systems, including mount types, permissions, standard tools, and effective pipeline utilization.

Skilled in Python programming for data manipulation, automation scripts, and Airflow DAGs, with foundational understanding of Perl.

Extensive practical experience with relational databases, particularly Oracle Exadata, optimizing complex queries and data structures.

Adept at designing and implementing data warehouses, possessing comprehensive knowledge of intricate data flows from source to consumption.

Applied Agile methodology consistently throughout the SDLC, contributing to collaborative and iterative project delivery and efficiency.

Driven by a passion for automation and continual process improvement, consistently seeking innovative solutions to enhance all data operations.

EDUCATION:

Master of Science in Big Data Analytics @ Pennsylvania State University TECHNICAL SKILLS:

Programming Languages: Python, Shell Scripting, SQL, Perl

Operating Systems: Linux, Unix

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

Data Warehousing: Data Warehousing Concepts, ETL, Data Modeling, Dimensional Modeling

ETL Tools: Informatica PowerCenter, AWS Glue, Azure Data Factory

Orchestration: Apache Airflow

Version Control: Git

Methodologies: Agile, SDLC

Cloud Platforms: AWS, Azure

Other Tools: JIRA, Confluence, Docker, Jenkins

WORK EXPERIENCE:

Senior Data Engineer @ Cigna Bloomfield, CT Sep 2024 – Present

Designed and implemented highly scalable data warehousing solutions on Linux-based infrastructure, processing large- scale healthcare data efficiently.

Developed complex ETL workflows using a combination of shell scripting, Python, and Informatica to ingest and transform data from diverse sources into the data warehouse.

Configured and managed Linux environments, including setting up file systems and permissions, to ensure secure and optimized data processing operations.

Enhanced various Linux-based toolsets, creating robust shell scripts for automating data loading, extraction, and transformation processes effectively.

Optimized Oracle Exadata database performance, developing advanced SQL queries and PL/SQL procedures for complex data transformations and aggregations.

Implemented and managed data pipelines using Apache Airflow with Python, orchestrating intricate ETL jobs for timely data delivery and reporting.

Ensured data quality and integrity by developing and implementing comprehensive validation frameworks within the Linux data processing ecosystem.

Collaborated with cross-functional teams to identify and implement significant system and architecture improvements for the data warehousing platform.

Leveraged Python for scripting custom data processing tasks, API integrations, and automating operational aspects within the Linux environment.

Maintained detailed documentation for Linux configurations, shell scripts, and ETL processes, ensuring knowledge transfer and system maintainability.

Participated actively in Agile sprints, utilizing JIRA for task management and fostering continual process improvement in data operations.

Provided expert support for data warehouse operations, troubleshooting Linux server issues and optimizing ETL job performance efficiently.

Technologies Used: Linux, Oracle Exadata, Shell Scripting, Python, Informatica PowerCenter, Apache Airflow, SQL, Data Warehousing, Git, Agile

Data Engineer @ U.S. Bank Minneapolis, MN Apr 2022 – Jul 2023

Implemented and managed Linux-based processes for critical financial data warehousing initiatives, ensuring high availability and performance standards.

Developed and enhanced complex ETL routines using shell scripting and Python to extract, transform, and load data into the Oracle data warehouse.

Configured and maintained Unix file systems, implementing secure data handling practices and managing permissions for sensitive financial information.

Applied practical knowledge of Unix tools and pipes to construct efficient data processing chains and automate repetitive data warehousing tasks.

Designed and optimized Oracle database schemas and stored procedures for financial reporting and analytical processing, enhancing query performance.

Utilized Informatica PowerCenter to develop robust ETL mappings and workflows, integrating diverse data sets for comprehensive data warehousing.

Collaborated with data architects to identify and implement system improvements, contributing to the overall scalability of the data warehousing platform.

Wrote Python scripts for data validation, automation of ETL processes, and generating alerts for data quality anomalies proactively.

Managed and orchestrated data pipelines using Apache Airflow, ensuring timely and accurate delivery of financial data for business intelligence.

Provided hands-on support for database load and extract processes, troubleshooting issues and implementing performance tuning strategies effectively.

Worked within an Agile methodology, actively participating in sprint planning, daily stand-ups, and code reviews to ensure project alignment.

Contributed to comprehensive documentation of ETL logic, database designs, and Linux system configurations using Confluence for knowledge sharing.

Technologies Used: Linux, Oracle, Shell Scripting, Python, Informatica PowerCenter, Apache Airflow, SQL, Unix, Data Warehousing, Azure DevOps, Agile

Junior Data Engineer @ Dollar Tree Chesapeake, VA Nov 2019 – Mar 2022

Developed and maintained ETL workflows using Informatica PowerCenter for retail data processing, handling large volumes of transactional data efficiently.

Extracted data from Oracle and MySQL databases, performing complex transformations to prepare data for the enterprise data warehouse.

Designed and optimized SQL queries and stored procedures in Oracle, supporting various reporting and analytical requirements effectively.

Implemented batch processing pipelines for large datasets, leveraging Unix shell scripting for automation and efficient job scheduling.

Gained practical experience with Unix file systems, understanding mount types, permissions, and utilizing standard tools for data manipulation.

Assisted in developing and enhancing database load and extract processes, ensuring efficient data flow into the data warehouse environment.

Contributed to data cleansing, transformation, and aggregation logic within the ETL framework, ensuring high data quality standards.

Supported production ETL jobs, performing debugging and root cause analysis to maintain data pipeline reliability and integrity.

Used Git for version control of ETL mappings and SQL scripts, ensuring collaborative development and robust change management practices.

Collaborated with business analysts to gather requirements and define data models, translating business needs into effective technical solutions.

Utilized Python for ad-hoc data analysis and scripting small automation tasks to support various ETL operations and data processing.

Participated in continuous improvement initiatives, streamlining existing data processes and enhancing overall data integrity and performance.

Technologies Used: Oracle, Informatica PowerCenter, MySQL, SQL, Unix, Shell Scripting, Python, Hadoop (HDFS, Hive), Git, Jenkins

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