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Senior Data Engineer || Ottawa/Toronto || Local only
- Toronto, ON, Canada
Contract
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- Job type
- Contract
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- Posting language
- English
- Posted
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Archived listing. The details below describe a past opening.
Role: Senior Data Engineer
Location: Ottawa/Toronto (Hybrid)
Must have : SQL+ Datawarehouse+ Banking domain
Job Description:
This position is for a Senior Data engineer with a background in Python, Pyspark, SQL and data warehousing for enterprise level systems. The position calls for someone that is comfortable working with business users along with business analyst expertise.
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:
· SQL Server based development of large datasets
· 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.
More about this job
Responsibilities
Build, optimize, and monitor data pipelines and Databricks Spark workloads for ingesting, transforming, and analyzing large datasets while maintaining data quality, security, and governance. Design enterprise data warehouse solutions, perform SQL development and code reviews, and collaborate with business users and analysts.
Requirements
Requires strong experience with Python, PySpark, SQL, data warehousing, and the banking domain, including enterprise data warehouse design and dimensional modeling. Candidates should also have experience with Databricks, cloud data warehouses, ETL, streaming technologies, and cloud data platform migration and architecture.
Skills
- SQL
- Python
- PySpark
- Databricks
- Data Warehousing
- ETL Pipelines
- Data Modeling
- Dimensional Modeling
- Delta Lake
- Apache Spark
- Data Integration
- Cloud Data Platforms
- Streaming Data
- SQL Server
- Data Quality
- Data Governance
Visa sponsorship
Not detected in the job text
Categories
- Data & Analytics
- Technology
- Software
- Finance & Accounting
Keywords
- SQL
- Python
- PySpark
- Databricks
- Apache Spark
- Delta Lake
- Data Warehousing
- Enterprise Data Warehouse
- ETL
- Data Pipelines
- Data Ingestion
- Data Transformation
- Data Loading
- Data Integration
- Data Modeling
- Dimensional Modeling
- OLTP
- OLAP
- SQL Server
- Stored Procedures
- Cloud Data Warehouse
- Azure Synapse
- BigQuery
- Amazon Redshift
- Snowflake
- Streaming Data
- Event-Based Processing
- Data Quality
- Data Governance
- Banking