Lokesh Ballani
Beaverton
Summary
Senior Data Engineer with extensive experience in designing efficient data pipelines and optimizing performance at Nike. Achieved a 95% improvement in data accuracy through rigorous quality assurance and collaboration. Proficient in Python and SQL, with a strong focus on implementing big data solutions and leading analytics initiatives.
Overview
9
9
years of professional experience
1
1
Certification
Work History
Senior Data Engineer
NIKE
Beaverton
02.2022 - Current
- As a Senior Data Engineer at Nike, I am responsible for designing and implementing data pipelines and data processing systems.
- I work with technologies such as Python, Apache Spark, Airflow, Databricks, SQL, Scala, Hadoop, and Apache Kafka to extract, transform, and load data from various sources.
- My responsibilities include:
- Collaborating with cross-functional teams to gather requirements and design data solutions.
- Developing and maintaining data pipelines using Python, Apache Spark, and Hadoop technologies.
- Creating Data bricks brick-flows, workflows, and Orchestrating data pipelines in Data bricks and Airflow.
- Creating Hive objects on top of S3 buckets.
- Creating data objects in Data bricks catalogs and familiar with Data bricks lake house architecture.
- Implementing data transformations and data integration processes to ensure data accuracy and integrity.
- Optimizing data pipelines for performance and scalability.
- Creating and maintaining documentation for data processes and workflows.
- Working with Data Analytics Managers to discuss the data analytics, research, and creating STMs for data products we build.
- Update data product STMs in Collibra for lineage and define the attribute naming convention as per Nike data governance.
- Implemented Spark expectations framework for data quality checks on the data pipelines using Spark which is an open source but modified to Nike standards.
- Familiar with Airflow Operators, connections, and variables.
Senior Data Engineer
Freddie Mac
McLean
01.2021 - 01.2022
- Used ETL to transform and clean data, improving data quality and accuracy by 95%.
- Built a data catalog to store metadata and enable data governance.
- Created a dashboard to represent key metrics and monitor system health visually.
- Deployed an analytics platform that enabled data scientists to access and analyze data easily.
- Developed a data lake architecture that allowed for efficient storage and retrieval of large datasets.
- Developed a data quality framework to standardize and validate data.
- Quality-assured data before loading into the data warehouse to ensure accuracy and completeness.
- Created data models and documented data flows to improve system architecture and data quality.
- Implemented a data governance framework to ensure data accuracy and quality, resulting in an 80% reduction in errors in reports.
Big Data Engineer
Columbia Sportswear
Portland
01.2019 - 01.2021
- Developed a data ingestion process to automate the transfer of data from multiple sources into a single database, resulting in a 100% reduction in manual data entry.
- Created data models and documented data flows to improve system architecture and data quality.
- Utilized data visualization tools to create interactive graphical representations of financial data.
- Developed and implemented a data backup and recovery system, increasing data security and reducing downtime in the event of a system failure.
- Built a data warehouse that stored and organized customer data, improving data accuracy by 99%.
- Created an automated data pipeline that reduced data processing time by 60%, allowing for faster analysis and decision-making.
- Collaborated with cross-functional teams to identify and resolve data-related issues, resulting in a 90% improvement in data accuracy.
- Designed and implemented a big data processing pipeline to transform and aggregate large datasets, resulting in a 20% improvement in processing time.
- Optimized database performance by designing efficient data models and indexing.
- Conducted a comprehensive analysis of customer demographics and purchasing behaviors, resulting in a targeted marketing campaign that increased sales by 25%.
- Performed statistical analysis and built predictive models to uncover trends in customer data, resulting in a 35% increase in sales.
- Developed a comprehensive data warehouse to store and manage large volumes of data.
- Utilized SQL to query and manipulate large datasets for analysis and reporting.
- Performed data mining to identify trends and patterns in customer data, which informed product development strategies.
Hadoop Developer
Otsuka
Princeton
01.2016 - 12.2018
- Developed a custom UI library that increased developer productivity and code reuse.
- Involved in the review of functional and non-functional requirements.
- Installed and configured Hadoop MapReduce HDFS.
- Developed multiple MapReduce jobs in Java for data cleaning and preprocessing.
- Installed and configured Pig and also wrote Pig Latin scripts.
- Wrote MapReduce job using Pig Latin.
- Involved in managing and reviewing Hadoop log files.
- Imported data using Sqoop to load data from MySQL to HDFS regularly.
- Developing Scripts and Batch Jobs to schedule various Hadoop Programs.
- Written Hive queries for data analysis to meet the business requirements.
- Creating Hive tables and working on them using Hive QL.
- Importing and exporting data into HDFS and Hive using Sqoop.
- Experienced in defining job flows.
- Got good experience with the NoSQL database SOLR HBase.
- Involved in creating Hive tables loading with data and writing Hive queries that will run internally in map reduce way.
- Developed a custom File System plug in for Hadoop so it can access files on the Data Platform.
- This plugin allows Hadoop Map Reduce programs HBase Pig and Hive to work unmodified and access files directly.
- Designed and implemented Map Reduce-based large-scale parallel relation-learning system.
- Extracted feeds from social media sites such as Facebook and Twitter using Python scripts.
- Set up and benchmarked Hadoop/HBase clusters for internal.
Education
Master's - Information Technology & Management
Campbellsville University
Campbellsville, KY12.2015
Skills
- SQL and NoSQL databases
- Data analysis and modeling
- Agile methodologies
- Business analysis and requirements
- Data engineering and integration
- Machine learning algorithms
- Performance optimization strategies
- Technical documentation and reporting
- Collaborative teamwork and communication
- Software troubleshooting and support
- Data pipeline design and management
- Big data processing technologies
- Cloud services (AWS)
- Containerization (Docker, Kubernetes)
- Continuous integration (CI/CD)
- Data quality assurance practices
- Hadoop architecture expertise
- Python programming skills
- Spark development and analytics
- JIRA project management
Certification
- GENERATIVE AI FOR BUSINESS WITH MSFT AZURE OpenAI PROGRAM - https://www.mygreatlearning.com/certificate/MAYYBBVK
- Academy Accreditation - Databricks Lakehouse Fundamentals
- Fundamentals of the Dbx lakehouse platform accreditation
Hobbies and Interests
- Snowboarding
- Hiking
- Travelling
- Camping
- Movies
Timeline
Senior Data Engineer
NIKE
02.2022 - Current
Senior Data Engineer
Freddie Mac
01.2021 - 01.2022
Big Data Engineer
Columbia Sportswear
01.2019 - 01.2021
Hadoop Developer
Otsuka
01.2016 - 12.2018
Master's - Information Technology & Management
Campbellsville University
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