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E-Solutions

Senior Data Engineer (banking Domain)

Toronto, ON, Canada

Contract

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Job details

Job type: Contract
Apply by: Nov 5, 2026
Experience: · 5+ years with Experience with developing and deploying ETL pipelines using Databricks Pyspark.
Posting language: English
Posted: Oct 6, 2026

Original job description

: Senior Data Engineer (banking Domain)

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

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More about this job

Responsibilities

Build, optimize, and monitor data pipelines and Databricks Spark workloads that ingest, transform, and process large volumes of data while maintaining data quality, security, and governance. Design enterprise data warehouse solutions and data models, troubleshoot performance issues, and review code for requirements fit and adherence to standards.

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, along with banking-domain and data warehousing experience. Candidates should be proficient in Python and SQL, have cloud data warehouse experience and strong architectural skills, and hold at least a bachelor's degree in engineering or computer science; a master's degree is strongly preferred.

Skills

SQL
Data Warehousing
Banking Domain
Python
PySpark
Databricks
ETL Pipelines
Data Integration
Cloud Data Warehousing
Dimensional Data Modeling
Delta Lake
Streaming Data
Data Quality
Data Governance
Enterprise Data Warehouse Design
Cloud Data Platform Migration

Visa sponsorship

Not detected in the job text

Keywords

SQL Server
SQL
Python
PySpark
Databricks
Apache Spark
Delta Lake
Data Warehousing
Enterprise Data Warehouse
ETL
Data Pipelines
Data Integration
Cloud Data Warehouse
Azure Synapse
BigQuery
Amazon Redshift
Snowflake
OLTP
OLAP
Dimensional Modeling
Facts and Dimensions
Data Modeling
Streaming Data
Structured Data
Semi-Structured Data
Unstructured Data
Data Quality
Data Security
Data Governance
Banking

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