Remote- full time- Posted July 27, 2026- via djinni.co
You will be redirected to djinni.co to apply.
We are looking for a Senior Data Engineer to design and build scalable data platforms that process large volumes of data for analytics, reporting, and business-critical applications.
You will work with distributed data processing systems, cloud infrastructure, streaming platforms, and modern data pipelines. We are looking for an engineer who can independently own production solutions and solve complex performance and architecture challenges.
Mandatory Skills
Programming & Data Processing
- Strong Python development skills
- Advanced SQL (complex queries, optimization, execution plans)
- Strong commercial experience with Apache Spark / PySpark
- Experience optimizing Spark jobs (partitioning, shuffle, joins, skew handling)
Data Engineering
- Experience building production-grade ETL / ELT pipelines
- Strong experience with Apache Airflow
- Strong hands-on experience with Apache Kafka
- Understanding of batch and streaming data processing architectures
Infrastructure & Storage
- Experience with relational databases (PostgreSQL, MySQL or similar)
- Data modeling and query optimization
- Hands-on experience with at least one cloud platform (AWS, Azure or GCP)
- Experience working with Docker, Linux, Git, and basic CI/CD pipelines
Desired Skills
- Databricks, Snowflake or similar cloud data platforms
- Kubernetes
- CDC pipelines (Debezium or similar)
- Modern analytical/storage systems (ClickHouse, Trino, Iceberg, Delta Lake)
- Monitoring tools (Grafana, Prometheus)
Responsibilities
- Build scalable batch and streaming data pipelines
- Develop and optimize Spark/PySpark data processing jobs
- Build Kafka-based ingestion and event-driven pipelines
- Design and maintain Airflow orchestration workflows
- Optimize SQL queries and improve pipeline performance
- Investigate production issues and improve system reliability
- Participate in architecture and technical design discussions
Senior-Level Expectations
- Independently design scalable data pipelines
- Debug and optimize distributed production systems
- Solve performance bottlenecks in Spark and SQL workloads
- Make technical decisions with minimal supervision
- Take ownership of production solutions end-to-end
Soft Skills
- Strong problem-solving skills
- Ownership and accountability
- Ability to work independently
- Good communication and collaboration skills
- Proactive engineering mindset
