Senior Data Engineer Linux & Data Warehousing Expert

Adarsh Malla — Senior Data Engineer

470-***-**** *************@*****.***

PROFESSIONAL SUMMARY:

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

Expert in designing and implementing scalable data solutions, focusing on performance optimization within diverse data warehouse environments.

Proficient in Shell Scripting and Python, automating complex ETL processes and system enhancements for operational efficiency.

Deep expertise in Oracle development, including Exadata environments, for advanced data warehousing and high- performance database operations.

Extensive practical experience in Linux environment setup, managing Unix file systems, and configuring critical data pipeline processes.

Skilled in enhancing ETL/database load/extract processes, ensuring data integrity and optimizing data flow for analytical consumption.

Adept at identifying and implementing system/architecture improvements, driving continuous integration and performance enhancements.

Experienced with leading orchestration tools like Apache Airflow for building robust, scalable data pipelines using Python for complex workflows.

Proven ability to work effectively within an Agile methodology, contributing to sprint planning and delivering high- quality data solutions.

Strong background in managing relational databases, particularly Oracle and PostgreSQL, for large-scale data storage and retrieval.

Committed to automation and continual process improvement, leveraging scripting and modern tools to streamline data operations.

Excellent communicator with strong written and oral skills, adept at conveying complex technical concepts to diverse stakeholders.

WORK EXPERIENCE:

Senior Data Engineer @ UnitedHealth Group — Minnetonka, MN June 2024 – Present

Designed and implemented Linux-based data warehousing processes, ensuring robust infrastructure for high-volume healthcare data operations.

Utilized Shell Scripting extensively to automate complex ETL/database load processes and system maintenance tasks across environments.

Managed and configured Oracle Exadata databases, optimizing performance for large-scale data warehousing and analytical queries.

Developed scalable data pipelines using Python and PySpark on AWS EMR, integrating various healthcare claims and EHR datasets effectively.

Orchestrated end-to-end data workflows with Apache Airflow using Python, implementing critical data quality checks and alerts proactively.

Enhanced ETL/database extract processes, ingesting diverse data formats from Oracle and other RDBMS into S3 for downstream consumption.

Identified and implemented system/architecture improvements within the AWS ecosystem, enhancing data flow efficiency and reliability continually.

Maintained Unix file systems and permissions, ensuring secure and compliant data storage and access for sensitive PHI according to policies.

Collaborated within an Agile framework, contributing to sprint planning and delivering continuous improvements to data warehouse infrastructure.

Leveraged Jenkins and Docker for CI/CD of data solutions, ensuring seamless deployment and operational stability of Linux-based applications.

Technologies Used: Linux, Shell Scripting, Oracle Exadata, Python, Apache Airflow, AWS (EMR, S3, Glue, Athena), PySpark, Oracle, Kafka, Jenkins, Docker, GitHub, Agile Data Engineer @ Walmart — Bentonville, AR Jan 2021 – Aug 2023

Managed Linux-based data warehousing infrastructure within the Azure environment, supporting large-scale retail analytics platforms reliably.

Developed comprehensive Shell Scripts to automate data loading, extraction, and transformation processes for customer behavior data.

Administered and optimized Oracle Exadata databases, enhancing query performance and data availability for critical business intelligence needs.

Designed and implemented scalable ETL pipelines using Azure Data Factory and Databricks, incorporating Python for complex data transformations.

Enhanced ETL/database load processes, integrating diverse retail data sources into ADLS and Azure Synapse for centralized data warehousing.

Utilized Informatica for migrating and transforming legacy data into the Azure cloud, ensuring data integrity and consistency across systems.

Identified and implemented system/architecture improvements within Azure, focusing on optimizing data flows and reducing processing times efficiently.

Applied practical knowledge of Unix file systems, including permissions and standard tools, to secure and manage retail datasets effectively.

Collaborated within an Agile methodology, actively participating in sprint cycles to deliver robust and efficient data warehouse solutions.

Streamlined data orchestration using Python, improving the reliability and observability of data pipelines for real-time demand forecasting.

Technologies Used: Linux, Shell Scripting, Oracle Exadata, Python, Informatica, Azure (ADLS, ADF, Databricks, Synapse, Event Hub), Scala, Teradata, Git, JIRA, Agile

Data Engineer @ Allstate Insurance — Northbrook, IL Jun 2019 – Dec 2020

Developed robust ETL pipelines using Informatica PowerCenter to integrate diverse claims and policy data from various sources efficiently.

Utilized Shell Scripting for automating batch job execution and monitoring, ensuring efficient data processing within the Linux environment.

Managed and optimized Oracle and PostgreSQL databases, implementing complex SQL and PL/SQL procedures for data transformation.

Enhanced ETL/database load processes, ingesting large volumes of data from APIs and flat files including CSV, XML, and JSON formats.

Worked extensively within the Hadoop ecosystem for initial batch transformations, leveraging Hive for structured data analytics and reporting.

Implemented data validation and quality rules, ensuring high accuracy and reliability of insurance datasets for critical reporting.

Maintained Unix file systems and permissions, ensuring secure handling of sensitive data and operational stability of systems.

Created and maintained Control-M workflows for scheduling critical data pipeline dependencies and ensuring timely data availability.

Collaborated within an Agile environment using ServiceNow and JIRA, contributing to continuous improvement of data engineering practices.

Migrated legacy Informatica mappings to modern Hadoop-based ingestion frameworks, improving scalability and processing efficiency.

Technologies Used: Linux, Shell Scripting, Informatica, Oracle, PostgreSQL, SQL, Hadoop, Hive, Control-M, Bitbucket, Jenkins, ServiceNow, JIRA, Agile

TECHNICAL SKILLS:

Programming Languages: Python, Shell Scripting, SQL, Perl, Scala

Databases: Oracle Exadata, Oracle, PostgreSQL, MySQL, Hive

Operating Systems & Utilities: Linux, Unix File Systems, Shell Environment, mount types, permissions, standard tools, pipes

ETL & Orchestration: Informatica, Apache Airflow, Azure Data Factory, Control-M

Cloud Platforms: AWS (S3, EMR, Glue, Athena), Azure (ADLS, ADF, Synapse)

Data Warehousing & Big Data: Data Warehousing, ETL, Data Modeling, Data Flows, Apache Spark, Databricks, Hadoop, Snowflake

Version Control & Project Management: Git, GitHub, Bitbucket, JIRA, Agile Methodology EDUCATION:

Masters in Management Information Systems @ University of Memphis

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