Lead the design and delivery of Databricks-based analytics platforms, guiding teams, and advising clients on best practices and migrations.
The Headlines...
Location - Hybrid in our Pune Office
A few application tips…
We want to help you put your best foot forward. Here are a few things we look for:
Location - Hybrid in our Pune Office
A few application tips…
We want to help you put your best foot forward. Here are a few things we look for:
- Clear, specific examples of your work and impact
- Relevant experience aligned with the role’s focus
- A thoughtful response to any application questions
- A resume that highlights both what you did and why it mattered
If you’re unsure whether your background is the “perfect fit,” we still encourage you to apply. We value potential and growth just as much as experience.
Why this role exists…
Why this role exists…
As Snap continues to scale, clients are investing heavily in modern data platforms built on Databricks. We’re supporting increasingly complex programmes, from enterprise migrations to capability‑wide Databricks enablement and we’re expanding our Databricks practice to meet this demand.
We’re looking for a Senior Data Platform Consultant with strong Databricks experience to join our Delivery team. This role is ideal for someone who enjoys shaping platform strategy, leading team delivery, and enabling others to grow their technical skills.
You’ll join a supportive, collaborative team where everyone’s perspective is valued. If you enjoy helping clients unlock the value of their data through modern engineering and thoughtful leadership, we’d love to hear from you.
You’ll also lead the design and delivery of complex Databricks‑based analytics platform solutions, while helping shape Snap’s growing Databricks capability. We’re looking for someone with strong Databricks expertise, collaborative leadership skills and the ability to shape client outcomes.
You’ll also lead the design and delivery of complex Databricks‑based analytics platform solutions, while helping shape Snap’s growing Databricks capability. We’re looking for someone with strong Databricks expertise, collaborative leadership skills and the ability to shape client outcomes.
You might be a great fit if you have:
You’ll lead the design and delivery of complex Databricks-based analytics
platform solutions, while helping shape Snap’s growing Databricks capability.
Your responsibilities will include:
• Leading the architecture and delivery of large-scale Databricks Lakehouse
solutions
• Driving Databricks migration and modernisation projects
• Advising clients on Databricks best practices, capability uplift and roadmap development
• Guiding cross-functional delivery teams and supporting capability growth
across engineering and analytics
• Establishing scalable patterns, reusable assets and improvements to
Databricks delivery approaches
• Coaching consultants and team leads on Databricks engineering,
governance, optimisation and platform design
• Contributing to Snap’s internal Databricks initiatives, thought leadership
and go-to-market strategy
In your first 3–6 months, success might look like:
• Leading the delivery of a strategic Databricks Lakehouse initiative
• Influencing a client’s data platform roadmap using Databricks expertise and commercial insight
• Supporting a team lead to strengthen Databricks capability and delivery
confidence
• Helping shape Snap’s Databricks frameworks, accelerators or internal best
practices
platform solutions, while helping shape Snap’s growing Databricks capability.
Your responsibilities will include:
• Leading the architecture and delivery of large-scale Databricks Lakehouse
solutions
• Driving Databricks migration and modernisation projects
• Advising clients on Databricks best practices, capability uplift and roadmap development
• Guiding cross-functional delivery teams and supporting capability growth
across engineering and analytics
• Establishing scalable patterns, reusable assets and improvements to
Databricks delivery approaches
• Coaching consultants and team leads on Databricks engineering,
governance, optimisation and platform design
• Contributing to Snap’s internal Databricks initiatives, thought leadership
and go-to-market strategy
In your first 3–6 months, success might look like:
• Leading the delivery of a strategic Databricks Lakehouse initiative
• Influencing a client’s data platform roadmap using Databricks expertise and commercial insight
• Supporting a team lead to strengthen Databricks capability and delivery
confidence
• Helping shape Snap’s Databricks frameworks, accelerators or internal best
practices
What you’ll need to succeed…
We’re looking for someone with strong Databricks expertise, collaborative
leadership skills and the ability to shape client outcomes.
You might be a great fit if you have:
• Deep, hands-on experience with Databricks, including:
o Lakeflow Jobs and Lakeflow Declarative Pipelines
o Autoloader and similar spark structured streaming patterns
o PySpark and Spark SQL
o Implementing CI/CD pipelines using Databricks Asset Bundles
o Unity Catalog and data governance including attribute based access
controls
• Strong knowledge of python and SQL
• Experience deploying and managing Databricks workspaces with IaC tools
like Terraform
• Strong experience in at least one cloud platform (Azure, GCP, AWS)
• Experience with enterprise extraction tools like Fivetran, HVR and Azure
Data Factory, and their integration with a Databricks platform
• Experience leading large, complex data platform deliveries
• Strong architectural thinking across ingestion, transformation,
modelling, orchestration and governance
• Clear communication skills and confidence working with a range of
stakeholders
• A practical, outcomes focused approach that connects technical delivery to business value
This role might not be the right fit if you’re looking for:
• A purely hands-on engineering role without strategic or client-facing
elements
leadership skills and the ability to shape client outcomes.
You might be a great fit if you have:
• Deep, hands-on experience with Databricks, including:
o Lakeflow Jobs and Lakeflow Declarative Pipelines
o Autoloader and similar spark structured streaming patterns
o PySpark and Spark SQL
o Implementing CI/CD pipelines using Databricks Asset Bundles
o Unity Catalog and data governance including attribute based access
controls
• Strong knowledge of python and SQL
• Experience deploying and managing Databricks workspaces with IaC tools
like Terraform
• Strong experience in at least one cloud platform (Azure, GCP, AWS)
• Experience with enterprise extraction tools like Fivetran, HVR and Azure
Data Factory, and their integration with a Databricks platform
• Experience leading large, complex data platform deliveries
• Strong architectural thinking across ingestion, transformation,
modelling, orchestration and governance
• Clear communication skills and confidence working with a range of
stakeholders
• A practical, outcomes focused approach that connects technical delivery to business value
This role might not be the right fit if you’re looking for:
• A purely hands-on engineering role without strategic or client-facing
elements
About
We're a high-growth data analytics consultancy on a mission to help enterprise businesses unlock the full potential of their data. With offices in the UK, India, and South Africa, we specialise in cutting-edge cloud analytics solutions, transforming complex data challenges into actionable business insights.We partner with some of the biggest brands worldwide to modernise their data platforms, enabling smarter decision-making through Snowflake, Databricks, Matillion, and other cloud technologies. Our approach is customer-first, innovation-driven, and results-focused, delivering impactful solutions with speed and precision.At Snap, we’re not just consultants, we’re problem-solvers, engineers, and strategists who thrive on tackling complex data challenges. Our culture is built on collaboration, continuous learning, and pushing boundaries, ensuring our people grow just as fast as our business.Join us and be part of a team that’s shaping the future of data analytics!
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