Databricks Engineer
- Toronto, ON, Canada
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Original job description
Role : Databricks Engineer
Location : Ottawa / Toronto (Hybrid)
The Cloud Data Engineer is responsible for designing, building, and maintaining scalable data pipelines and Azuer cloud platforms. This role involves working with large datasets, optimizing data workflows, and ensuring secure, efficient data storage and processing in cloud environments.
Major Responsibilities:
- Build and optimize data pipelines for efficient data ingestion, transformation and loading from various sources while ensuring data quality and integrity.
- Design, develop, and deploy Spark program in databricks environment to process and analyze large volumes of data.
- Experience of Delta Lake, DWH, Data Integration, Cloud, Design and Data Modelling.
- Proficient in developing programs in Python and SQL
- Experience with Data warehouse Dimensional data modeling.
- Working with event based/streaming technologies to ingest and process data.
- Working with structured, semi structured and unstructured data.
- Optimize Databricks jobs for performance and scalability to handle big data workloads.
- Monitor and troubleshoot Databricks jobs, identify and resolve issues or bottlenecks.
- Implement best practices for data management, security, and governance within the Databricks environment. Experience designing and developing Enterprise Data Warehouse solutions.
- Proficient writing SQL queries and programming including stored procedures and reverse engineering existing process.
- Perform code reviews to ensure fit to requirements, optimal execution patterns and adherence to established standards.
Skills:
- 5+ years Python coding experience.
- 5+ years - SQL Server based development of large datasets
- 5+ years with Experience with developing and deploying ETL pipelines using Databricks Pyspark.
- Experience in any cloud data warehouse like Synapse, Big Query, Redshift, Snowflake.
- Experience in Data warehousing - OLTP, OLAP, Dimensions, Facts, and Data modeling.
- Previous experience leading an enterprise-wide Cloud Data Platform migration with strong architectural and design skills.
- Experience with Cloud based data architectures, messaging, and analytics.
- Cloud certification(s).
- Any experience with Airflow is a Plus.
Education
- Minimally a BA degree within an engineering and/or computer science discipline
- Master’s degree strongly preferred
More about this job
Responsibilities
Design, build, and optimize scalable data pipelines and cloud data platforms, using Databricks and Spark to ingest, transform, and process large datasets. Monitor and troubleshoot jobs, improve performance, and apply data quality, security, governance, and code review practices.
Requirements
The role requires at least five years of Python, SQL Server development, and experience building and deploying ETL pipelines with Databricks PySpark. A bachelor's degree in engineering or computer science is the minimum stated education requirement, while a master's degree is strongly preferred; cloud data warehousing, data modeling, cloud architecture, and migration experience are also sought.
Skills
- Python
- SQL
- SQL Server
- Databricks
- PySpark
- ETL Pipelines
- Data Warehousing
- Data Modeling
- Delta Lake
- Apache Spark
- Cloud Data Platforms
- Data Integration
- Streaming Data
- Data Security
- Data Governance
- Airflow
Visa sponsorship
Not detected in the job text
Categories
- Data & Analytics
- Technology
- Software
- Engineering
Keywords
- Databricks
- PySpark
- Apache Spark
- Python
- SQL
- SQL Server
- ETL
- Data Pipelines
- Delta Lake
- Data Warehousing
- Enterprise Data Warehouse
- Data Modeling
- Dimensional Modeling
- OLTP
- OLAP
- Cloud Data Platforms
- Cloud Data Architecture
- Data Integration
- Streaming Data
- Event-Based Processing
- Structured Data
- Semi-Structured Data
- Unstructured Data
- Data Quality
- Data Security
- Data Governance
- Synapse
- BigQuery
- Redshift
- Snowflake