Aditya Singh

WORK HISTORY

EDUCATION

ABOUT ADITYA SINGH

As a passionate sports enthusiast, I\'ve always been fascinated by the numbers behind the game—trending charts, stats, and player performances. My curiosity about how analytics shape insights led me to dive deeper, uncovering the backbone of it all: raw data. The journey from discovering where this data originates to understanding how it\'s transformed fueled my passion for Data Engineering.In my data engineering journey, I’ve worked on ETL job design, workflow automation, job scheduling, and monitoring mission-critical data pipelines. I specialize in transforming raw data into actionable insights, ensuring stakeholders and BI tools get the right data at the right time.Tech Stack:Scripting: Python, Shell, PySpark, Django FrameworkDatabases & Data Warehouses: Snowflake, Redshift, MySQL, PostgreSQL, DynamoDB, BigQuery, HDFS, AWS S3, MongoDB, GraphDB (Neo4j), Metadata layers(Delta Lake, HUDI)Workflow Management: Airflow, Jenkins, Glue Workflow, Databricks WorkflowProcessing Tools: Databricks, Flink, AWS Glue, dbt, AWS Lambda, EMR, EC2(compute power)Real-time data feeds: Apache Kafka, AWS KinesisCI/CD & Infrastructure: Jenkins, CircleCI, GitHub Actions, Terraform, CloudFormationCloud Platforms: AWS, GCPFile Formats: Parquet, Avro, ORC, CSV, JSONAlerting & Monitoring, Logging: SNS, PagerDuty, Prometheus, CloudwatchBI & Analytics: Tableau, Looker, Qlik, GrafanaMy journey in data engineering is one of continuous learning and growth. I\'m always exploring new tools, technologies, and best practices to refine my craft and push the boundaries of what’s possible with data.