🇮🇳 Sandeep Rawat — Data Engineer

Experienced Database Architect with over 15 years of expertise in designing and managing both OLTP and OLAP databases. Adept at defining robust data models, implementing security measures, developing archival strategies, and creating monitoring dashboards, alerting systems, and performance benchmarking tools. Proficient in optimizing batch and streaming data pipelines using Apache Spark, with a strong focus on code optimization and efficiency. Developed and implemented rules and processes to maintain high data quality and ensure accurate data lineage throughout the data lifecycle. Possesses hands-on experience with multiple AWS services and NoSQL databases like MongoDB and DynamoDB. Successfully delivered cross-technology platform migrations, leveraging reusable templates to accelerate subsequent migration modules. DBMS: SQL Server, MySQL, PostgreSQL NoSQL: MongoDB, Redis, Cassandra Scripting: Python Cloud: AWS (EC2, S3, Redshift, Data Pipeline, Snowflake, EMR) Big Data: Hive, Spark, Scala Data Modeling: Star and Snowflake Schema BI Tools: SSIS, SSRS, Data Extraction Data Modeling Tools: Power Designer Version Control: Git, Perforce, TFS, VFS StackOverflow Profile:  http://stackoverflow.com/users/6085803/sandeep-rawat (Top 9% Overall) Data Management: Extensive experience in acquiring, validating, and managing large structured and unstructured datasets. Database Optimization: Skilled in optimizing procedures, functions, views, and ETLs to enhance system performance and scalability. Machine Learning: Deep understanding of supervised, unsupervised, and reinforcement learning methods. Proficient in data mining, predictive modeling, and data visualization using Python and PySpark. Work • Optimized Spark jobs to improve processing efficiency and reduce execution time and hardware cost. • DB design to support micro-service modeled application, applying ledger principles. • Load testing framework to benchmark performance across DB engines. • Dashboard creation to track procedure performance. • Setting up pipeline support using DMS for downstream accessibility of data from the PCI zone. • ETL was created to support the process for Certificates generation, as part of the legal compliance process. • Mongo DB cluster creation, setting up dashboards & alerting. • Upgrading Mongo versions and also upgrading security for Mongo clusters. Data corrections with improvements with indexing strategy. • Optimized procedures, functions, views, and ETL to enhance system performance and efficiency.

Stackforce AI infers this person is a Data Engineering expert in SaaS environments with strong database architecture skills.

Location: Gurgaon, Haryana, India

Experience: 19 yrs 4 mos