Data Engineer
- Toronto, ON, Canada
Contract
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Job details
- Job type
- Contract
- Apply by
- Experience
- · 5+ years with Experience with developing and deploying ETL pipelines using Databricks Pyspark.
- Posting language
- English
- Posted
Original job description
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:
· 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.
Education
- Minimally a BA degree within an engineering and/or computer science discipline
- Master’s degree strongly preferred
More about this job
Responsibilities
Build, optimize, and monitor data pipelines and Databricks Spark workloads for large-scale data ingestion, transformation, and analysis while maintaining data quality, security, and governance. Design enterprise data warehouse solutions, perform data modeling and SQL development, troubleshoot performance issues, and review code for quality and standards compliance.
Requirements
Requires at least five years of SQL Server development with large datasets and at least five years developing and deploying ETL pipelines using Databricks and PySpark. Candidates should have enterprise data warehousing, dimensional modeling, cloud data warehouse, and architectural or migration experience, along with a minimum bachelor's degree in engineering or computer science; a master's degree is strongly preferred.
Skills
- SQL
- Python
- PySpark
- Databricks
- Data Warehousing
- ETL Pipelines
- Data Modeling
- Delta Lake
- Data Integration
- Cloud Data Platforms
- Apache Spark
- Streaming Data
- SQL Server
- Data Quality
- Data Governance
- Banking
Visa sponsorship
Not detected in the job text
Categories
- Data & Analytics
- Technology
- Software
- Finance & Accounting
Keywords
- SQL
- Python
- PySpark
- Databricks
- Apache Spark
- Delta Lake
- SQL Server
- ETL
- Data Pipelines
- Data Warehousing
- Enterprise Data Warehouse
- Dimensional Modeling
- Data Modeling
- OLTP
- OLAP
- Facts and Dimensions
- Data Integration
- Cloud Data Platform
- Cloud Data Warehouse
- Synapse
- BigQuery
- Redshift
- Snowflake
- Streaming Data
- Event-Based Processing
- Structured Data
- Semi-Structured Data
- Unstructured Data
- Data Quality
- Banking