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Senior Data Engineer – Banking

E Solutions Global — Canada · Posted ~5 hours ago

Senior Hybrid

Skills

Python PySpark SQL Data warehousing Data pipelines Databricks Spark Data integration Data modeling Dimensional modeling Data quality Streaming data Business analysis Delta Lake Data Warehouse Cloud Streaming

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Summary ✨ AI‑Generated

Join a senior data engineering team building enterprise-scale pipelines and data platforms for a highly regulated financial environment. You will develop Python and SQL solutions, process large datasets with Spark and Databricks, design dimensional data models, support streaming ingestion, and collaborate closely with business stakeholders.

Highlights

Senior data engineering role focused on enterprise-scale banking systems, large-volume data processing, and modern data platforms. The position combines hands-on engineering with business-user collaboration and offers exposure to Databricks, cloud technologies, streaming, and advanced data modeling.

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