Senior Data Engineer (Contract, Full-Time) [HR208]

Smart Working; India; On-site; INR 4,000,000 - 9,000,000; Full time

Job summary

Smart Working is seeking a Senior Data Engineer to lead the data infrastructure powering an AI assistant for property managers and build-to-rent teams. You will architect scalable pipelines, enable real-time processing and ensure governance across the platform.

As the first senior data hire, you will define data architecture, tooling, standards and the hiring bar, while partnering with founders and product leadership to translate data capabilities into product decisions.

Qualifications

• 7+ years in data engineering or related roles.
• Strong experience with building data pipelines and distributed data systems.
• Relational databases experience, PostgreSQL preferred; MySQL acceptable.
• NoSQL databases experience required.
• Experience with vector databases used in AI systems.
• Proficient in Python for data processing and backend tasks.
• Ability to justify architectural decisions and design data models.
• Experience with Spark, Airflow, Kafka, Elasticsearch/OpenSearch is desirable.

Responsibilities

• Architect and build scalable data pipelines and infrastructure to support AI and product systems.
• Design and maintain data ingestion, transformation and storage architectures for operational and AI workloads.
• Develop and manage batch and real-time data pipelines.
• Build and optimise systems for vector search, retrieval and machine learning data pipelines.
• Ensure data reliability, security and governance across the platform.
• Collaborate with AI and backend engineering teams to support training, inference and product features.
• Implement monitoring, observability and data quality frameworks.
• Optimise the performance of large-scale datasets and query systems.
• Contribute to technical architecture decisions and long-term data strategy.
• Act as the founding data hire, defining culture, standards and the hiring bar for the data function as it scales.
• Partner directly with founders and product leadership to translate data capabilities into product decisions.

Skills

Python

Data pipelines

Distributed systems

PostgreSQL

NoSQL databases

Vector databases

Data modeling

Backend engineering

ML data workflows

Architectural decisions

Tools

Spark

Apache Airflow

Kafka

Elasticsearch/OpenSearch

Qdrant/Milvus/pgvector

Pandas/Polars

Job description

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 Senior Data Engineer, you will build and lead the data infrastructure powering an intelligent AI assistant that automates operational workloads for property managers, letting agents and build-to-rent teams. The platform manages communications, compliance, maintenance coordination and scheduling, helping property businesses operate with the efficiency of modern digital platforms.

You will architect and scale the systems behind the AI products, spanning real-time data pipelines, analytics infrastructure, vector databases and machine learning data workflows. Working closely with AI engineers, backend engineers, product teams, founders and product leadership, you will ensure the platform can process large volumes of operational data reliably and intelligently.

As the first senior data hire, you will define the data architecture, tooling, engineering standards, culture and hiring bar, building the foundations of the future data team.

Responsibilities

• Architect and build scalable data pipelines and infrastructure to support AI and product systems.
• Design and maintain data ingestion, transformation and storage architectures for operational and AI workloads.
• Develop and manage batch and real-time data pipelines.
• Build and optimise systems for vector search, retrieval and machine learning data pipelines.
• Ensure data reliability, security and governance across the platform.
• Collaborate with AI and backend engineering teams to support training, inference and product features.
• Implement monitoring, observability and data quality frameworks.
• Optimise the performance of large-scale datasets and query systems.
• Contribute to technical architecture decisions and long-term data strategy.
• Act as the founding data hire, defining culture, standards and the hiring bar for the data function as it scales.
• Partner directly with founders and product leadership to translate data capabilities into product decisions.

Requirements

• 7+ years of professional experience, with the majority of that experience in dedicated data engineering roles.
• Strong experience designing and building data pipelines and distributed data systems.
• Experience working with relational databases, with PostgreSQL preferred, although MySQL or similar is acceptable.
• Experience working with NoSQL databases.
• Experience with vector databases used in modern AI systems.
• Strong programming experience in Python.
• Demonstrated ability to make and justify architectural decisions, rather than only implementing them.
• Experience building scalable backend systems.
• Experience designing data models and storage architectures.
• Strong understanding of data processing performance and optimisation.
• Experience with some of the following data frameworks and infrastructure technologies is highly desirable: Apache Spark, Apache Airflow, Kafka, and Elasticsearch or OpenSearch.
• Experience with relevant database technologies is highly desirable, including PostgreSQL, MongoDB, and vector databases such as Qdrant, Milvus or pgvector.
• Experience with Python data-processing libraries such as Pandas or Polars is highly desirable.

Nice to Have

• Experience working on AI or machine learning platforms.
• Familiarity with stream processing and event-driven architectures.
• Experience with cloud infrastructure such as GCP, AWS or Azure.
• Experience working in high-growth startups or early-stage companies.

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 judgement. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.