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Spark Eighteen

Data Engineer - Senior II

New Delhi, INIn sedeIndeterminatoTempo pieno

Pubblicato il 30 set 2026

Questa offerta è pubblicata in EN

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


Informazioni ruolo

Tipo di lavoro

Tempo pieno

Skill richieste

Apache Airflow pipeline design and managementApache Spark batch processing and optimizationKafka streaming architecture and ingestionObject storage (AWS S3 / MinIO) managementPython programming for data engineeringSQL and PostgreSQL development and tuningPostGIS and geospatial data processingTimescaleDB and time-series data managementDocker and Docker Compose deployment (including air-gapped)Design and implementation of data ingestion, transformation, and bulk-loading pipelinesData observability, lineage, performance monitoring, and SLA complianceData platform architecture and scalable pipeline designStakeholder management and translating business requirements into data products

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