Senior Data Engineer - SaaS (Data architecture/ Startup)
PeopleGene
- Location
- Delhi, India
- Job type
- Full-time
Required skills
- Python
- Airflow
- AWS
- Apache
- Apache Airflow
- compliance
- data architecture
- data modeling
- data models
- end-to-end
- ETL
- Kafka
- Spark
About the role
Website:
peoplegene.in
Job details:
Responsibilities:
- Own end-to-end data architecture across ingestion, transformation, storage, and analytics
- Design and scale batch and streaming pipelines using Python, Airflow, Spark / PySpark, Kafka, dbt, and Debezium
- Architect and optimize data models across MongoDB, ClickHouse, and OpenSearch for high-volume ingestion and low-latency analytics
- Establish strong data quality, validation, and lineage practices using Great Expectations or similar frameworks
- Build clean, well-documented, analytics-ready datasets that power dashboards and AI workflows
- Mentor and guide a team of data engineers, setting standards and driving execution
- Partner closely with product, AI, and platform teams to enable new data use cases and faster experimentation
- Continuously improve performance, reliability, and cost efficiency on AWS
Good to have:
- 4 years of experience in data engineering/ architecture or data platform roles
- At least 2 years of experience leading or mentoring engineers
- Strong hands-on expertise in Python, Apache Airflow, Spark / PySpark, and MongoDB
- Solid understanding of ETL / ELT patterns, streaming systems, CDC, and scalable data modeling
- Experience designing systems that balance flexibility, performance, and data quality
- Working knowledge of AWS and production performance tuning
- Exposure to supply chain, procurement, pricing, or marketplace data
- Experience with data contracts, observability, or data SLAs
- Familiarity with privacy and compliance concepts such as GDPR or India DPDP
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