Senior 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)
Hire Type: Contract
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, ensuring data quality, performance, scalability, security, and governance. Develop enterprise data warehouse solutions, review code, troubleshoot processing issues, and collaborate with business users.
Requirements
Requires at least five years of SQL Server development and experience building and deploying ETL pipelines with Databricks and PySpark, along with strong SQL, Python, data warehousing, and data modeling skills. A bachelor's degree in engineering or computer science is the minimum stated education requirement; 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
- Data Quality
- Data Governance
- SQL Server
- 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
- Data Integration
- Dimensional Modeling
- OLTP
- OLAP
- Facts and Dimensions
- Cloud Data Warehouse
- Microsoft Synapse
- BigQuery
- Amazon Redshift
- Snowflake
- Streaming Data
- Event-Based Processing
- Structured Data
- Semi-Structured Data
- Unstructured Data
- Data Quality
- Data Security
- Data Governance
- Banking