DeepIntent is the leading healthcare marketing platform, purpose-built to help marketers plan, activate, and optimize data-driven campaigns with speed and precision. Trusted by the world’s top healthcare brands and their agencies, DeepIntent uniquely unites media, identity, and real-world clinical data to power privacy-safe, omnichannel marketing across every screen. Backed by patented technology and proven outcomes, DeepIntent’s platform delivers measurable audience quality and script lift at scale. Learn more at www.deepintent.com .
What You’ll Do:
Setting up formal data practices for the company.
Building and running super stable and scalable data architectures.
Design, develop, and maintain scalable, high-throughput backend services and REST APIs using Java and Spring Boot.
Designing and delivering solutions for low-latency data problems at scale.
Making it easy for folks to add and use new data with self-service pipelines.
Getting DataOps practices in place.
Designing, developing, and running data pipelines to help out Products, Analytics, data scientists and machine learning engineers.
Creating simple, reliable data storage, ingestion, and transformation solutions that are a breeze to deploy and manage.
Writing and Managing reporting API for different products.
Implementing different methodologies for different reporting needs.
Develop event-driven and asynchronous services using messaging and streaming platforms such as Kafka, alongside other datastores.
Follow and uphold engineering best practices around API design, code quality, testing, security, and data privacy, with healthcare compliance expectations in mind.
Use AI across the SDLC - design, coding, testing, reviews, and documentation to deliver production-grade data solutions, owning the review, testing, and debugging of all AI-generated code.
Teaming up with all sorts of people – business folks, other software engineers, machine learning engineers, and analysts.
Who You Are:
Bachelor’s degree in engineering (CS / IT) or equivalent degree from a well-known Institute / University.
3.5+ years of experience managing data at scale and building and running both batch and streaming data pipelines.
Experience with public clouds like GCP or AWS.
Experience with Apache open-source projects like Spark, Kafka, Druid, Airflow, and big data databases like BigQuery, Clickhouse.
Experience making data architectures that are optimised for both performance and cost.
Solid grounding in microservices, REST API design, and distributed systems fundamentals; GraphQL or gRPC exposure is a plus.
Experience with relational and NoSQL databases (e.g., PostgreSQL, MySQL, Aerospike, or similar), including schema design and query optimisation.
Good grasp of software engineering, DataOps, data architecture, Agile, and DevOps.
Proficient in SQL, Java, Spring Boot, Python, and Bash.
Good communication skills for working with technical and non-technical people.
Someone who takes ownership of problems and is solution-oriented — starts from the problem and the outcome, not just the ticket.
AI-native delivery skillset — has shipped real work using AI across the SDLC (design, coding, testing, reviews, documentation), not just experimented with it.
Hands-on with agentic coding tools (Claude Code, Cursor, Copilot, or similar), and quick to pick up new ones.
Treats AI as a pair programmer, not a threat or a shortcut — and owns the output: can review, test, and debug AI-generated code, because “the AI wrote it” is never an excuse.
Strong fundamentals in system design, data structures, and clean architecture.
Understands security and data-privacy guardrails when using AI tools, particularly given the healthcare data we work with.
Someone who thinks big, takes chances, innovates, dives deep, gets things done, hires and develops the best, and is always learning and curious.
We believe great work starts with great support. That’s why DeepIntent offers a competitive, holistic benefits package designed to…