Kumar Abhishek

About Kumar Abhishek

Results-driven Senior Data Engineer with 8.5+ years of experience designing and implementing data solutions to enhance organizational efficiency and decision-making. Proficient in data engineering, Python, AWS, Databricks, Spark, SQL, Airflow, Hadoop, Kafka, and Jenkins CI/CD pipelines, with a proven ability to develop reliable frameworks for high-quality data management. Expertise in designing scalable data architectures, optimizing data workflows, and improving data accessibility. Recognized for effective collaboration with cross-functional teams to streamline system onboarding and facilitate seamless data integration, leveraging analytics to drive business growth through innovative data strategies- Data Engineering- Amazon AWS (PaaS, SaaS, IaaS)- Python Programming, Java, Shell/Bash- DataBricks, DeltaLake, Delta Table- Spark, PySpark, Hive, SQL, Impala, Solr, Kafka, Sqoop, HDFS, Hadoop- MySQL, PostgreSQL, Oracle, PL/SQL, SQL- Airflow, Databricks, Netflix Genie, Oziee - Docker, Kubernetes, Terraform, Jenkins- Ranger, Kereberos, CrowdStrike, JWT, OAuth- Development, DevOps, GitOps, Support- Monitoring and Logging: Kibana, SignalFx, Splunk, Cloudwatch- Git, Bitbucket, SVN, TortoiseHg- VS Code, Pycharm, Eclipse, IntelliJ, Jupyter, KubeFlow, Hyperflow, Hue, Presto, Zeppelin, Athena- Apache, Tomcat, uWSGI/Nginx- AWS, EMR, Redshift, Glue, EC2, EBS, S3, IAM, Lambda, ECR, EKS, DynamoDB, RDS, Cloudformation, CloudWatch, ELB, API Gateway, SQS, SNS, SSM, SG, VPC, etc.

Experience

1. Senior Data Engineer - Enterprise Data Analytics & Artificial Intelligence

   Nike

   Aug 2022 — Present · Bengaluru, IN

   Data Quality:Customized the great-expectations library and integrated it with Nike\'s managed-spark framework to enable dynamic data quality rule ingestion via Excel.Contributed to the development of Nike\'s proprietary Spark-expectations framework, which performs in-flight data quality checks during pipeline execution.Infrastructure Cost & Utilization:Designed and developed TechSolution ID, a unique identifier for data products, enabling scalable measurement of engineering metrics across tools and processes.Telemetry:Implemented telemetry to monitor and analyze data usage and performance metrics, providing insights into access patterns and frequency.Nike Direct Clickstream:Worked on processing and building foundational layer with clickstream data generated by users navigating Nike.com, Nike App & SNKRS App to derive actionable insights into user behavior, enabling business teams to optimize digital experiences, improve marketing strategies, and enhance product development.Third-Party Partners(3PP):Onboarded eCommerce platform data from third-party partners (3PP) operating outside the Nike ecosystem onto the Nike Data Foundation.Ensured the availability of complete, trusted, and high-quality data to support global and APLA demand forecasting, enabling data-driven decision-making for teams across Operations.Databricks Workflow Dependency Sensor:Developed a custom operator to bridge Airflow DAG dependencies with Databricks Workflows, addressing challenges faced during the migration of pipelines to the new Databricks platform. This solution ensured seamless integration with downstream teams still operating on Airflow/EMR.Nike.net Product Recommendations:Built a foundational data layer using Adobe Clickstream data for product offerings and add-to-cart activity from Nike.net partners, enabling AI/ML teams to train models for recommendation engines, driving personalized user experiences & business growth.

Education

• Biju Patnaik University of Technology, Odisha

  Bachelor's degree

  2012 — 2016

• Jawahar Navodaya Vidyalaya - JNV

  Secondary Education, Mathematics and Science

  2005 — 2010

• Sree Ayyappa Public School

  Higher Secondary Education, Mathematics and Science

  2010 — 2012