Big Data Engineer

Senior Big Data Engineer Spark | Python | Databricks | Azure/AWS

Job Title: Senior Big Data Engineer L3/L4
Industry: IT Services & Consulting
Employment Type: Full-time, Permanent
Work Mode: Work from Office
Job Location: Gurugram
Experience: 614 Years
Salary: 3046 LPA
Open Positions: 7
Joining: Immediate to 30 Days Preferred

Job Summary

We are hiring experienced Big Data Engineers with strong expertise in Apache Spark, Python, Databricks, and cloud-based data engineering platforms.

The ideal candidates should have extensive hands-on experience in designing, developing, and optimizing large-scale distributed data processing systems. Strong expertise in PySpark, distributed computing, ETL pipelines, and cloud data platforms is essential.

Candidates must have mandatory hands-on experience with Databricks on Azure or AWS.

We have multiple openings at L3 and L4 engineering levels, offering opportunities for both experienced individual contributors and senior engineers with technical leadership capabilities.

Key Responsibilities

• Design, develop, and implement scalable Big Data solutions using Apache Spark and Python.
• Build, maintain, and optimize distributed data processing pipelines.
• Develop batch and real-time data processing solutions.
• Work with Azure Databricks or AWS Databricks for large-scale data engineering workloads.
• Perform Spark job optimization, performance tuning, and troubleshooting.
• Build streaming data pipelines using Kafka, Spark Streaming, or similar technologies.
• Develop ETL workflows and integrate data from multiple sources, including RDBMS, ERP systems, and files.
• Work with SQL and NoSQL databases for large-scale data processing.
• Collaborate with cross-functional engineering teams to design and implement data solutions.
• Follow Agile development methodologies and engineering best practices.
• Senior-level candidates should be capable of leading technical teams and driving solution design.

Mandatory Technical Skills

• Apache Spark / PySpark
• Python Programming
• Azure Databricks or AWS Databricks
• Azure or AWS Cloud Data Services
• Distributed Computing
• ETL Development and Data Pipelines
• SQL – Queries, Joins, Stored Procedures, and Relational Schemas
• Spark Performance Tuning

Additional Technical Skills

• Hadoop v2, MapReduce, HDFS, and Sqoop
• Apache Kafka and RabbitMQ
• Apache Storm and Spark Streaming
• Hive and Impala
• NoSQL databases – HBase, Cassandra, and MongoDB
• SQL Server and Oracle
• Delta Lake and Spark SQL

Candidate Requirements

• 6–14 years of overall IT experience.
• Minimum 6 years of relevant experience in Big Data and data engineering.
• Strong understanding of distributed computing principles.
• Expert-level knowledge of Apache Spark.
• Hands-on programming experience with Python.
• Mandatory practical experience with Databricks on Azure or AWS.
• Experience designing and implementing enterprise-scale Big Data solutions.
• Strong problem-solving and analytical skills.
• Ability to work independently and collaborate with engineering teams.
• Senior candidates should have experience leading technical teams.

Compensation

• L3: 30–35 LPA | 6–9 Years
• L4: 40–46 LPA | 8–14 Years

Final compensation will depend on experience, technical expertise, and interview performance.

Joining Preference

Immediate joiners to candidates with a maximum 30-day notice period.

Interview Details

• Face-to-Face Interview Drive
• Date: 14 November 2026
• Location: Gurugram

How to Apply

Interested candidates can share their updated resumes at:

adithyaa@riosintelli.com

Please mention the following details in your email:

• Current CTC
• Expected CTC
• Total Experience
• Relevant Big Data Experience
• Databricks Experience (Azure/AWS)
• Current Location
• Notice Period / Expected Joining Date
• Availability for F2F drive on 14th November, Saturday 2026 - Yes/No
• What are your preferred work locations, name at least 3 cities

Important: Hands-on Databricks experience with Azure or AWS is mandatory. Candidates without practical Databricks experience will not be considered.