Staff Data Engineer (Remote, Full-Time) [HR139]

About Smart Working

At Smart Working, we believe your job should not only look right on paper but also feel right every day. This isn’t just another remote opportunity - it’s about finding where you truly belong, no matter where you are. From day one, you’re welcomed into a genuine community that values your growth and well-being.

Our mission is simple: to break down geographic barriers and connect skilled professionals with outstanding global teams and products for full-time, long-term roles. We help you discover meaningful work with teams that invest in your success, where you’re empowered to grow personally and professionally.
Join one of the highest-rated workplaces on Glassdoor and experience what it means to thrive in a truly remote-first world.

About the role

As a Staff Data Engineer, you will play a pivotal role in shaping and evolving a cloud-based data platform that underpins data-driven decision-making across the business. You’ll lead the design, build, and optimisation of scalable data pipelines, data models, and data quality controls, working closely with data analysts and business stakeholders to turn data needs into reliable, high-impact solutions.

This is a senior, hands-on role suited to an engineer who enjoys ownership, technical leadership, and working in a fast-growing environment. The data platform has evolved significantly over the past five years and will continue to do so, including a planned transition towards Google BigQuery over the next 12–18 months, making this an exciting time to join and influence long-term direction.

Responsibilities:
• Design, build, and maintain a cloud-based data platform that supports analytics, MI, and insight for internal and external stakeholders
• Lead the development and optimisation of data pipelines, ensuring they are scalable, reliable, and performant
• Own and evolve data models, enabling consistent and trusted reporting across the business
• Implement and improve data quality controls, monitoring accuracy, completeness, and reliability
• Collaborate closely with data analysts and business stakeholders to translate data requirements into technical solutions
• Support the ongoing evolution of data ingestion and integration solutions as the platform scales
• Contribute to technical decision-making and best practices across the data engineering function
• Play a key role in the transition from Azure-based data services to Google BigQuery, helping shape future architecture

Requirements:
• Strong experience designing and maintaining cloud-based data platforms in a production environment
• Proven ability to build and optimise data pipelines and ingestion processes
• Solid experience with data modelling for analytics and reporting use cases
• Experience implementing data quality frameworks and controls
• Background working closely with data analysts and non-technical stakeholders, translating business needs into data solutions
• Hands-on experience with cloud data technologies, with exposure to either Azure or Google Cloud platforms
• Comfortable working in an environment where the data platform is continuously evolving

Nice to have:
• Experience with or strong interest in Google BigQuery and large-scale analytical workloads
• Prior involvement in cloud platform migrations or major data architecture changes
• Experience supporting MI, analytics, or insight teams in a fast-growing business
• Background in insurance, fintech, or other highly data-driven industries

Benefits:
• Fixed Shifts: 12:00 PM - 9:30 PM IST (Summer) | 1:00 PM - 10:30 PM IST (Winter)
• No Weekend Work: Real work-life balance, not just words
• Day 1 Benefits: Laptop and full medical insurance provided
• Support That Matters:Mentorship, community, and forums where ideas are shared
• True Belonging: A long-term career where your contributions are valued

At Smart Working, you’ll never be just another remote hire.

Be a Smart Worker - valued, empowered, and part of a culture that celebrates integrity, excellence, and ambition.

If that sounds like your kind of place, we’d love to hear your story.