Senior Databricks Engineer / Data Architect

🔹 1. Basic Information

Job Title*

Senior Databricks Engineer / Data Architect

Company*

Cogentix Systems

Location*

Gurugram, Chennai, Hyderabad, Bangalore, Mumbai, Pune

Work Type*

Hybrid (3 Days Work From Office / 2 Days Work From Home)

Street Address*

Client Office – Technology & Analytics Center

Area / Neighborhood*

IT Park / SEZ / Business District

City*

Gurugram, Chennai, Hyderabad, Bangalore, Mumbai, Pune

🔹 2. Job Requirements

Required Skills*

• Databricks
• Apache Spark
• PySpark
• Data Architecture
• ETL / ELT Pipelines
• Data Modeling
• SQL

Preferred Skills*

• Azure Databricks / AWS Databricks
• Delta Lake
• Data Warehousing
• Azure Data Factory / Airflow
• Cloud Data Platforms

Nice-to-Have Skills

• Machine Learning Pipelines
• CI/CD for Data Engineering
• Terraform
• Data Governance & Security

Total Experience (In Years)*

Minimum: 10

Maximum: 18

Educational Qualification*

• B.E / B.Tech
• MCA
• M.Tech
• M.Sc (Data Science / Computer Science)

Language Requirements*

• English (Mandatory)

Age Range*

Minimum: 28

Maximum: 48

🔹 3. Job Terms & Compensation

Employment Type*

Contract to Hire (C2H)

Category*

IT / Data Engineering & Analytics

Currency*

INR (₹)

Salary Range*

Minimum: ₹20,00,000 per annum

Maximum: ₹26,00,000 per annum

Number of Openings*

4

Shift Timings*

Uk Shift

Tenure (Days)*

90

Payment Frequency*

Yearly

Hiring Need*

Immediate

🔹 4. Job Description & Publishing

Job Description*

Cogentix Systems is seeking a highly experienced Senior Databricks Engineer / Data Architect to design, build, and optimize scalable data platforms for enterprise analytics and reporting. This role requires deep expertise in Databricks, Spark, and modern cloud-based data architectures.

Key Responsibilities

• Design and implement scalable data architectures using Databricks
• Build and optimize ETL/ELT pipelines using Spark and PySpark
• Develop and manage Delta Lake-based data platforms
• Ensure data quality, performance, and reliability across pipelines
• Collaborate with data scientists, analysts, and business teams
• Implement data security, governance, and access controls
• Optimize query performance and cost efficiency
• Lead architecture decisions and mentor junior data engineers
• Integrate CI/CD pipelines for data engineering workflows

Who Should Apply

• Professionals with 10+ years of data engineering and architecture experience
• Strong hands-on expertise in Databricks and Spark
• Experience designing enterprise-scale data platforms
• Comfortable working in a hybrid model