Build and maintain scalable data platforms, including Airflow ingestion pipelines, Kafka streaming, Spark workloads, data lakes, and database solutions. Develop secure, containerized applications for air-gapped environments; optimize ingestion, queries, and production performance. Ensure data quality, lineage, observability, and SLA compliance while translating customer needs into data products. Create documentation and operational runbooks, troubleshoot production issues, and collaborate with engineers, analysts, and business stakeholders.
We’re passionate about building seamless digital experiences powered by robust and intelligent data systems. We’re on the lookout for a Data Engineer - Senior to architect and maintain high-performance data platforms that fuel decision-making and innovation.
If you enjoy designing scalable pipelines, optimising data systems, and leading with technical excellence, you’ll thrive in our fast-paced, outcome-driven culture.
You’ll take ownership of building reliable, secure, and scalable data infrastructure - from streaming pipelines to data lakes. Working closely with engineers, analysts, and business teams, you’ll ensure that data is not just available, but meaningful and impactful across the organization.
Requirements
- 5+ years of experience in Data Engineering and production-scale data platforms.
- Design and manage Apache Airflow pipelines for high-volume sensor, satellite, and third-party data ingestion.
- The project requires experience with Object Storage (such as AWS S3 or MinIO), Kafka streaming, and familiarity with an Ubuntu environment.
- Build and optimize Apache Spark workloads for batch processing, geospatial analytics, and large-scale aggregations.
- Develop and maintain PostgreSQL, TimescaleDB, PostGIS, and DuckDB-based data solutions.
- Implement efficient data ingestion, transformation, and bulk-loading pipelines.
- Containerize and deploy applications using Docker and Docker Compose, including air-gapped environments.
- Collaborate with customer teams to translate business requirements into data products and analytical solutions.
- Ensure data quality, lineage, observability, performance, and SLA compliance.
- Troubleshoot production issues and optimize pipeline, database, and query performance.
- Create and maintain technical documentation, data models, and operational run-books.
- Demonstrate strong proficiency in Python, SQL, Airflow, Spark, and PostgreSQL.
- Experience with geospatial and time-series data, S3-compatible storage, and secure customer environments.
- Strong communication, stakeholder management, and problem-solving skills.
Benefits
- Comprehensive insurance coverage that gives you peace of mind, so you can focus on doing your best work
- Flexible work arrangements designed to support sustained productivity, personal well-being, and work-life balance
- Continuous learning and accelerated skill development through hands-on projects and mentorship from experienced industry leaders
- Global client exposure across 20+ countries, offering real-world experience with diverse markets and business environments.
- Opportunity to work on high-impact, large-scale projects that have collectively generated over $1B in measurable business value
- Competitive, market-aligned compensation packages that recognize performance, expertise, and long-term contribution
- Monthly demo days that celebrate innovation, showcase your work, and give you a real voice in what we build
- Annual recognition programs and performance-driven awards in a truly meritocratic environment
- Referral bonuses that reward you for helping grow a strong, like-minded team
- A strong problem-solving culture with opportunities to tackle meaningful, real-world challenges
- A positive, people-first workplace that supports happiness, balance, and long-term growth
Spark Eighteen New Delhi, Delhi, IND Office
New Delhi, India
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