Parallel Score is a product development firm that develops data and user-centric solutions by leveraging design, engineering, and innovative thinking. We are a provocative product development agency that is focused on imagining and building highly-interactive and user- driven experiences that push the limits of user design and development.
Job overview
- We are looking for a Data Engineer experienced in Databricks and cloud-native data architecture to build scalable data pipelines and optimize analytics workflows.
- You will ensure that data is reliable, accessible, and efficiently processed for analytical and AI initiatives.
Responsibilities
- Design, build, and maintain ETL/ELT pipelines using Databricks (PySpark, Delta Lake).
- Integrate and transform data from diverse structured and unstructured sources.
- Implement data quality, monitoring, and governance processes.
- Optimize data storage and compute performance in AWS, Azure, or GCP.
- Collaborate with data scientists and analysts to support advanced modeling and BI.
Required Skills & Experience
- 5+ years in data engineering or big data development.
- Hands-on expertise in Databricks, Apache Spark, and SQL.
- Strong coding ability in Python and familiarity with data orchestration tools (Airflow, dbt).
- Experience with data lakehouse architectures and CI/CD pipelines.
Preferred:
- Relevant Cloud certification
- Knowledge of Delta Live Tables, streaming data (Kafka), or machine learning integration in Databricks.
Method of application
Meet the Qualifications? Apply now at Parallel Score on portal.parallelscore.com