Business Unit:
Cubic Transportation Systems
Company Details:
The Senior Data Engineer will play a key role in designing, building, and maintaining scalable data pipelines, integrations, and analytical platforms that support CTS’s global analytics and reporting platforms. This role is responsible for developing high-quality ETL/ELT processes, managing cloud data environments, ensuring data quality, and enabling advanced analytics and reporting across major programs.
You will work extensively with Azure Data Factory, Azure Databricks, Python, SQL (Oracle/SQL Server), data modelling, data lakes, and enterprise data warehouse structures to support KPI engines, device analytics, predictive modelling, and operational performance insights.
Job Details:
Key Responsibilities
The following are the key responsibilities of the position. It is expected that most, if not all of these, are met by the candidate:
· Design, build, and optimize data pipelines using Azure Data Factory and Databricks (pyspark/spark SQL).
· Develop robust ETL/ELT processes to ingest, transform, and validate large volumes of operational, telemetry, incident, and transactional data.
· Implement scalable workflows leveraging Azure services such as Data Lake Storage, Azure Synapse, Azure SQL Databases, Key Vault, Logic Apps, and Functions.
· Build efficient advanced SQL queries and stored procedures across Azure Synapse and Azure SQL Server.
· Collaborate with data analysts, engineers, performance assurance, and operations teams to enable reliable, accurate datasets for reporting, KPIs and predictive analytics.
· Design and maintain data models, schemas, tables, and metadata following COE architecture patterns.
· Implement strong data quality, validation, and monitoring frameworks to ensure accuracy and reliability across global programs.
Required Skills and Qualifications
· Bachelor’s/master’s degree in Comp Science, Data Analytics, Engineering, Mathematics, or related field.
· 5+ years of experience in data engineering roles.
· Strong expertise with Azure Data Factory (ADF) pipelines, Azure Databricks, mapping data flows, and orchestrations.
· Advanced experience with Azure Databricks (pyspark, spark SQL, Delta Lake, notebooks, clusters).
· High proficiency in Python for ETL, automation, and data transformation.
· Strong SQL skills across Azure Synapse and Azure SQL including query tuning and complex transformations.
· Solid understanding of data modelling, warehousing, star/snowflake schema, Medallion architecture and distributed data processing.
· Experience handling large-scale datasets and complex data domains.
· Familiarity with CI/CD practices, Git branching, and DevOps pipelines.
· Experience with data governance, data cataloging, and managing structured/unstructured data in cloud environments.
Preferred Skills
· Experience with Azure Data Factory (ADF) pipelines, Azure Databricks, Databricks Workflows, or Apache Airflow.
· Exposure to real-time/streaming data technologies (Event Hub, Kafka, Spark Streaming).
· Exposure to Machine learning algorithms, feature engineering, model evaluation, hyperparameter tuning, LLM fundamentals and scikit-learn/XGBoost. Knowledge with deep learning, PyTorch/TensorFlow, MLflow, model deployment, and MLOps practices.
· Experience integrating APIs, flat files, and operational systems such as ServiceNow.
· Experience to machine learning pipelines, feature stores, or model operationalization.
· Familiarity with Power BI dataset design and optimization.
· Understanding of multi-region cloud environments and enterprise architecture patterns.
Soft Skills
· Strong analytical mindset with exceptional problem-solving abilities.
· Ability to work independently and take ownership of deliverables.
· Excellent communication…