Data Engineer

We are hiring for Data Engineer

R Systems International!!!

As discussed regarding the job opportunity for Data Engineer.

Please go through the below details (about the company, Client, and Job description).

About- R Systems International Limited (https://www.rsystems.com/about-us/factsheet/)

R Systems is a Blackstone portfolio Company founded in 1993, Headquartered at El Dorado Hills, California, United States (USA) and offshore delivery centers located at Noida, Pune and Chennai.

R Systems International Limited is listed publically at NSE and BSE with current share price at around RS 500+. It is a leading digital product engineering company that designs and builds next-gen products, platforms, and digital experiences empowering clients across various industries to overcome digital barriers, put their customers first, and achieve higher revenues as well as operational efficiency. We constantly innovate and bring fresh perspectives to harness the power of the latest technologies like cloud, automation, AI, ML, analytics, Mixed Reality etc.

Location

Job Description for Sr Data Engineer

Year Experience : 7+ Years

ADF, DataBricks, SQL, Data Modeling

Senior Consultant - Data Engineer

Data Engineering & Architecture:

• Design, develop, and deploy

  high-performance data pipelines

  using

  Azure Data Factory (ADF), Databricks, and PySpark/Scala

  .
• Implement

  batch and real-time data processing

  solutions on

  Azure Synapse, Delta Lake, and Azure SQL DB

  .
• Optimize

  Spark jobs

  for performance tuning, partitioning, and cost efficiency in

  Databricks

  .
• Architect

  medallion (bronze, silver, gold) data lakehouse

  frameworks for structured and unstructured data.
• Develop

  data ingestion, transformation, and orchestration

  workflows using

  ADF, Databricks Notebooks, and Azure Functions

  .

Collaboration & Leadership:

• Work closely with

  data scientists, analysts, and business stakeholders

  to deliver scalable data solutions.
• Mentor junior engineers and provide technical guidance on best practices.
• Lead

  proof-of-concepts (POCs)

  and evaluate new data technologies.
• Document architecture, data flows, and best practices for knowledge sharing.