Senior Data Engineer ETL, Linux, Oracle, Airflow

Vikas Yedavelly — Senior Data Engineer

720-***-**** ***************@*****.***

PROFESSIONAL SUMMARY:

Adept Senior Data Warehouse Engineer with 5+ years of expertise in designing, implementing, and managing robust Linux-based data warehousing infrastructures.

Proficient in enhancing ETL and database load/extract processes, ensuring optimal performance and data integrity for enterprise-scale solutions.

Expert in Shell Scripting and Python, developing intricate automation scripts to streamline data operations and improve system efficiency.

Extensive experience with relational databases, including practical application of Oracle development and Exadata for high-performance data management.

Skilled in identifying and implementing system and architecture improvements to enhance scalability, reliability, and maintainability of data platforms.

Deep understanding of Unix file systems, including mount types, permissions, standard tools, and effective utilization of pipes for complex data manipulation.

Proven ability to manage and configure Linux-based processes, ensuring stable and efficient data flow within warehousing environments.

Experienced in utilizing ETL tools like Informatica to construct comprehensive data pipelines, driving efficient data integration and transformation.

Practical working knowledge of orchestration tools such as Airflow with Python for scheduling and monitoring complex data workflows effectively.

Committed to Agile methodologies, consistently delivering iterative improvements and collaborating cross-functionally to achieve project goals.

Passionate about automation and continual process improvement, consistently seeking innovative solutions to optimize data warehousing operations.

Adept at transforming complex data into actionable intelligence, leveraging strong analytical skills and a deep understanding of data warehousing principles.

TECHNICAL SKILLS:

Programming & Scripting: Python, Shell Scripting, Perl, SQL, PySpark, Scala

Data Warehousing & Databases: Oracle Exadata, Oracle, Synapse, Snowflake, Redshift, SQL Server, Relational Databases

ETL & Orchestration: Informatica, Airflow, Azure Data Factory, SSIS

Operating Systems & Utilities: Linux, Unix File Systems, PowerShell

Cloud Platforms: Azure (Databricks, Synapse, Purview, Event Hubs), AWS (Glue, Redshift, S3)

DevOps & Automation: Azure DevOps, Terraform, Jenkins, Git, CI/CD

Methodologies & Governance: Agile/Scrum, Data Governance, Metadata-Driven ETL, HIPAA, SOX, PCI-DSS, GDPR

Business Intelligence & Tools: Power BI, Tableau, Looker, JIRA, Confluence WORK EXPERIENCE:

Senior Data Engineer @ Old National Bank — Evansville, IN Jan 2024 – Present

Implemented and managed Linux-based processes and infrastructure to support an enterprise data warehouse, ensuring high availability and robust performance.

Developed and enhanced complex Shell Scripting solutions for automating data ingestion, transformation, and database load/extract operations.

Optimized data warehousing architecture on Azure, incorporating Oracle Exadata best practices for high-volume financial transaction processing.

Engineered end-to-end ETL pipelines using Azure Data Factory and Informatica, integrating diverse financial data into a centralized data lakehouse.

Designed and maintained Oracle databases for core banking systems, developing stored procedures and optimizing queries for critical reporting and analytics.

Enhanced various Linux-based toolsets, scripts, and jobs to streamline data quality checks and governance frameworks, adhering to SOX and PCI-DSS compliance.

Utilized Python within Databricks to process and curate large datasets, integrating with orchestration tools like Airflow for scheduled workflows.

Collaborated with cross-functional teams using Agile methodologies to identify and implement system improvements, delivering measurable enhancements to data reliability. Technologies Used: Linux, Shell Scripting, Oracle Exadata, Informatica, Azure Data Factory, Databricks, Synapse, Python, Azure DevOps, Terraform

Data Engineer @ Molina Healthcare — Long Beach, CA Dec 2022 – Dec 2023

Architected and managed Linux-based data processing environments within Azure, consolidating claims and eligibility data across multiple healthcare systems.

Developed robust Shell Scripting routines for automating daily data synchronization, file transfers, and system health checks on Unix file systems.

Designed and implemented ETL frameworks using Informatica and Azure Data Factory to ingest, cleanse, and transform millions of healthcare records daily.

Managed and optimized Oracle databases supporting clinical and patient outcome data, ensuring data integrity and high- performance querying capabilities.

Leveraged Python and PySpark in Databricks to build scalable data pipelines, enhancing data quality and preparing curated datasets for analytics and reporting.

Implemented system and architecture improvements for data warehousing solutions, focusing on enhancing reliability and efficiency of database load/extract processes.

Partnered with data governance teams to maintain HIPAA standards, utilizing data lineage and classification tools like Azure Purview for audit readiness.

Enhanced various Linux-based scripts and jobs to automate data validation and reconciliation processes, ensuring 99.9% data accuracy across all pipelines.

Technologies Used: Linux, Shell Scripting, Oracle, Informatica, Azure Data Factory, Databricks, Synapse, Python, Unix File Systems, Azure Purview, Azure DevOps

Data Engineer @ Liberty Mutual Insurance — Boston, MA Jun 2020 – Jun 2022

Managed and configured Linux-based infrastructure supporting critical insurance data warehouses, ensuring stable operations for actuarial and business analytics.

Developed and maintained complex Shell Scripting solutions for automating data extraction, transformation, and loading into various database platforms.

Built and managed ETL pipelines using Informatica and Azure Data Factory, integrating claims, underwriting, and policy data from diverse sources including Oracle.

Implemented system/architecture improvements for data processing workflows, optimizing database load/extract processes for large datasets and enhancing data refresh cycles.

Designed and optimized data models in Oracle and SQL Server for insurance analytics dashboards, improving insights into policy performance and claims turnaround efficiency.

Utilized Python scripts for automating auditing and reconciliation processes, ensuring data consistency across multiple insurance systems and environments.

Enhanced various Linux-based toolsets and jobs for data quality validation and monitoring, improving SLA compliance and data accuracy.

Collaborated with DevOps teams to implement CI/CD automation for data pipelines, ensuring repeatable and reliable deployments across environments.

Technologies Used: Linux, Shell Scripting, Oracle, Informatica, Azure Data Factory, SQL Server, Python, Unix File Systems, Azure DevOps

EDUCATION:

Lindsey Wilson University @ Master's in Technology Management

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