Senior Data Engineer

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