DevOps Engineer
Summary
A senior, hands-on data platform role (posted as DevOps Engineer) owning end-to-end architecture and delivery of lakehouse/warehouse platforms: building pipelines, Spark and SQL transformations, data models, governance, and Power BI semantic layers on Databricks and Microsoft Fabric for client data transformation projects, fully remote from India.
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.
- 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.
- 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.
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.
Benefits:
Skills
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