DevOps Engineer

Jobgether; India; Remote; INR 2,800,000 - 4,200,000; Full time

Benefits offered by this job

Fully remote

Flexible work environment

Professional development

Home office support

Wellness budget

Paid time off

Job summary

Jobgether in India seeks a Senior DevOps Engineer to design and build scalable data platforms for analytics. This hands-on role covers lakehouse and warehouse architectures, data ingestion, governance, automation, and analytics delivery, with a strong focus on Databricks and Microsoft Fabric.

You will own technical decisions, develop pipelines, and collaborate with clients and internal teams to translate requirements into scalable designs, applying CI/CD practices and ensuring governance and

Qualifications

• 8+ years of experience in data engineering with architecture ownership.
• Hands-on experience building production data platforms.
• Experience with Databricks or Microsoft Fabric and Spark/SQL.

Responsibilities

• Own the end-to-end data platform architecture and delivery.
• Write and deploy data pipelines, Spark and SQL transformations, and production models.
• Review and contribute to code from other team members.
• Design and implement lakehouse architectures using Databricks or Fabric.
• Establish medallion architectures, Delta tables, and semantic layers.

Skills

Databricks

Microsoft Fabric

Apache Spark

SQL

Python

Data governance

CI/CD

Power BI

Delta Lake

Lakehouse patterns

Unity Catalog

Purview

Azure Data Factory

Synapse

Azure SQL

Tools

Databricks

Job description

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a DevOps Engineer based in India.

As a DevOps Engineer, you will design and build scalable data platforms that support modern analytics and business intelligence environments. This is a hands-on architecture role where you will own technical decisions while actively developing pipelines, transformations, data models, and production code. You will work across lakehouse and warehouse architectures, ingestion, governance, automation, and analytics delivery. The role requires strong expertise in Databricks and Microsoft Fabric, alongside deep knowledge of Spark, SQL, Python, and modern data engineering practices. You will balance client workloads, licensing, technical capabilities, and cost considerations to build practical solutions. This is an opportunity to work on complex data transformation projects in a flexible, remote environment with significant ownership and professional development opportunities.

Accountabilities

You will own the end-to-end architecture and hands-on delivery of modern data platforms, ensuring they are scalable, governed, reliable, and aligned with business and technical requirements.

• Own the end-to-end data platform architecture, covering ingestion, lakehouse and warehouse layers, transformation, modeling, and delivery to reporting and analytics tools.
• Write and deploy data pipelines, Spark and SQL transformations, and production data models.
• Review and contribute to code developed by other members of the data engineering team.
• Design and implement lakehouse architectures using Databricks, Microsoft Fabric, or a combination of both.
• Establish medallion architectures, Delta table designs, and semantic layers appropriate to business requirements.
• Evaluate Databricks and Microsoft Fabric based on workloads, existing licensing, team capabilities, and cost considerations.
• Design and implement data ingestion from databases, SaaS applications, APIs, files, and legacy systems.
• Establish and maintain data governance and access-control frameworks using technologies such as Unity Catalog, Purview, or equivalent platforms.
• Apply governance, classification, lineage, cataloging, and access controls consistently throughout the platform.
• Design dimensional and semantic data models and establish clear principles for where business logic should reside.
• Support Power BI and ensure semantic models are structured appropriately for reporting and analytics.
• Apply CI/CD, version control, and testing practices across data engineering workflows.
• Collaborate with clients and internal teams to translate business requirements into scalable technical solutions.

Requirements

The ideal candidate combines senior-level data engineering experience with proven architecture ownership and a strong willingness to remain hands-on throughout the development lifecycle.

• 8+ years of experience in data engineering, including at least 3 years owning architecture and design decisions.
• Proven hands-on experience designing and building production-grade data platforms.
• Deep hands-on experience with Databricks or Microsoft Fabric, along with working knowledge of the other platform.
• Ability to clearly evaluate where Databricks, Fabric, or a hybrid approach is most appropriate.
• Strong experience with Apache Spark and SQL.
• Strong Python or equivalent production programming experience.
• Production experience with Delta Lake, medallion architecture, and lakehouse patterns.
• Experience with Power BI, including semantic model design and appropriate placement within the data architecture.
• Strong dimensional and semantic modeling skills, with the ability to establish and explain data modeling principles.
• Working knowledge of data governance, including data classification, lineage, cataloging, and access control.
• Experience applying CI/CD, version control, and testing practices to data engineering.
• Azure Government or GCC High delivery experience is a plus.
• Experience implementing Unity Catalog or Microsoft Purview is desirable.
• Familiarity with Azure Data Factory, Synapse, or Azure SQL is advantageous.
• Consulting or client-facing delivery experience is a plus.
• Experience working in regulated environments with significant compliance requirements is desirable.
• Databricks or Microsoft certifications are an advantage.

Benefits

• Competitive total rewards: A comprehensive compensation and rewards package.
• Fully remote: Work from home with no daily requirement to travel to an office, provided you have a stable internet connection.
• Flexible work environment: Support for maintaining a healthy balance between professional and personal life.
• Professional development: Substantial training allowance, professional development days, training opportunities, and support for industry certifications.
• Home office support: Company-provided equipment, including a laptop with your choice of operating system, plus an annual budget to personalize your workspace.
• Wellness budget: Annual allowance that can be used for fitness, gym memberships, massages, and other wellness activities.
• Paid time off: Generous paid vacation and sick leave.
• Volunteer day: Time off to support a charity or cause of your choice.
• Collaborative environment: Opportunity to work alongside experienced data, cloud, and technology professionals.
• Flexible career growth: Opportunities to strengthen existing expertise or develop new technical capabilities.

We appreciate your interest and wish you the best!

Data Privacy Notice:

By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.