Position: Lead Data Engineer

Job Type: Full Time Contract

Location: Mississauga, ON (Hybrid)

Must Have: Azure DevOps and azure data engineering, SSIS, Databricks

Must Have

As our new Data Engineer, you will play a role in designing, developing, and maintaining our data architecture on the Azure platform. You can expect to collaborate with cross-functional teams, leverage

your technical proficiency, and contribute to the successful implementation of data solutions.

What will you be doing?

Design and implement scalable, reliable, and high-performance data architectures on the Azure
Cloud platform.
Collaborate with data architects and other stakeholders to define data requirements and
architecture standards.
Develop end-to-end data pipelines, ensuring efficient and reliable data movement across
various stages, from ingestion to consumption.
Utilize Azure Data Factory, Azure Databricks, and other relevant services to orchestrate and
optimize data workflows.
Design and implement data models that support business requirements and enable efficient
querying and analysis.
Optimize data storage and retrieval processes for performance and cost-effectiveness.
Integrate diverse data sources into a unified data platform, ensuring data consistency, accuracy,
and reliability.
Implement data integration patterns using Azure services such as Azure Data Factory, Azure
Logic Apps, and Azure Functions.
Ensure compliance with data governance and privacy regulations.
Monitor data pipeline performance and proactively identify and resolve bottlenecks or issues.
Implement performance tuning strategies to optimize data processing and reduce latency.
Document data engineering processes, data flows, and system architecture for knowledge
sharing and future reference.

What experience do you have?

Bachelor’s degree in computer science, Information Technology, or a related field.
Proven experience (3+ years) as a Data Engineer, with a focus on Azure Cloud technologies.
In-depth knowledge of Azure services such as Azure Data Factory, Azure Databricks, Azure
Synapse Analytics, and Azure Storage.
3-5+ years experience working with large volumes of data (structured and unstructured).
Strong proficiency in programming languages such as Python, SQL, and familiarity with tools like
Spark.
Hands on experience on designing, developing, and implementing Enterprise Data Warehousing,
ETL and real-time/batch data exchanges and working with related technologies such as SSIS,
Azure Data Factory, Synapse Spark, Azure DevOps, Databricks.
Strong SQL skills, knowledge of RDBMS and Data Lake concepts.
Strong knowledge of data warehousing architecture, data mining methodologies and business
intelligence.
Knowledge of AI and ML developments/solutions/implementations is a plus.
Knowledge of data security, compliance, and governance best practices.

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Lead Data Engineer