Senior Data Software Engineer/ Databricks, Apache Spark, PySpark

Job description

We are seeking a skilled Senior Data Software Engineer with strong expertise in PySpark, SQL, and unit testing to join our data engineering team. The ideal candidate will have hands-on experience with Apache Spark, preferably within the Databricks environment, and will be responsible for building scalable data pipelines, optimizing data workflows, and ensuring code quality through rigorous testing practices.

Responsibilities

- Design, develop, and maintain scalable data pipelines using Apache Spark (Databricks preferred)

- Write efficient and optimized PySpark code for data transformation and processing

- Develop and execute complex SQL queries for data extraction, validation, and reporting

- Implement unit tests using pytest to ensure code reliability and maintainability

- Collaborate with data scientists, analysts, and other engineers to deliver high-quality data solutions

- Monitor and troubleshoot data workflows and performance issues

- Document technical designs, processes, and best practices

Requirements

- 3+ years of experience in Data Software Engineering

- Proven experience with Apache Spark, ideally in a Databricks environment

- Proficiency in PySpark and SQL

- Background in unit testing frameworks, especially pytest

- Understanding of data engineering principles and ETL processes

- Familiarity with version control systems (e.g., Git)

- Ability to work independently and in a collaborative team setting

- Excellent problem-solving and communication skills

- Proficiency in English at an Upper-Intermediate level (B2) or higher

Nice to have

- Experience with cloud platforms (e.g., Azure, AWS, GCP)

- Knowledge of CI/CD pipelines and DevOps practices

- Familiarity with Delta Lake, MLflow, or other Databricks-native tools