Senior Data Analytics Engineer

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The Senior Data Engineering & Analytics Specialist is responsible for designing, building, and optimizing scalable data platforms and analytical solutions that enable high-quality, data-driven decision-making. This role supports the full lifecycle of enterprise data assets—ranging from ingestion and transformation to modeling, analytics, and visualization—across hybrid cloud and on‑prem environments.

The ideal candidate combines strong data engineering expertise, deep SQL Server dashboarding, cloud knowledge, and practical analytics skills, enabling them to translate complex business requirements into reliable data pipelines, performant data models, and actionable insights.

Key Responsibilities

Data Engineering & Pipeline Development

• Design, build, and maintain robust, scalable ETL/ELT pipelines to ingest, transform, and load data from diverse sources, including IBM Netezza, and cloud-based platforms.
• Create and maintain optimal data pipeline architectures that support large-scale analytical workloads and evolving business needs.
• Implement incremental loads, change data capture (CDC), and data staging strategies to ensure process efficiency, reliability, and data integrity.
• Identify and implement process improvements, including automation, performance optimization, and infrastructure redesign for scalability.

Database & Platform Engineering

• Configure and optimize SQL Server environments for high-throughput analytical use cases, including parallel query execution, and indexing strategies.
• Design and implement partitioned tables, indexed views, and columnstore indexes to support large datasets and complex analytical queries.
• Manage and support SQL Server recovery models (Simple, Full, Bulk-Logged), including backup/restore strategies, log management, and disaster recovery planning.
• Support hybrid cloud and on‑prem data platforms, ensuring secure, efficient, and cost-effective data access.

Data Architecture & Modeling

• Design and maintain star and snowflake schemas, fact/dimension models, and slowly changing dimensions (SCDs).
• Translate business requirements into scalable, analytics-ready data models.
• Apply strong understanding of RDBMS, NoSQL concepts, and data formats such as CSV, Parquet, and JSON.
• Partner with data governance and data strategy teams to improve data quality, consistency, and usability.

Analytics, Reporting & Insights

• Develop and maintain Power BI dashboards using DAX and M Code to deliver actionable insights into customer behavior, operational performance, and key business metrics.
• Apply data analytics techniques to identify trends, anomalies, and opportunities for optimization.
• Collaborate with stakeholders to understand analytical needs and support data-driven decision-making.

Collaboration & Stakeholder Support

• Work closely with business partners, analysts, and technical teams to support data-related initiatives and resolve complex issues.
• Communicate technical concepts clearly to both technical and non-technical audiences.
• Exercise sound judgment to independently solve complex problems within established standards and governance frameworks.

Required Skills & Experience

Programming & Tools

• Strong programming skills in Python, SAS, and SQL.
• Experience with Power BI, including DAX and M Code.
• Proficiency with Microsoft 365 tools: Office, Power Automate, SharePoint, OneDrive.

Database & Data Engineering

• Advanced SQL Server configuration for analytical workloads.
• Experience designing high-performance data structures (partitioning, indexing, columnstore).
• Strong understanding of backup, recovery, and disaster recovery strategies.
• Hands-on experience building enterprise-grade ETL pipelines for large datasets.

Data Architecture

• Proven experience with dimensional modeling (star/snowflake, facts/dimensions, SCDs).
• Strong understanding of data integration, data warehousing, and enterprise data management.
• Ability to translate complex business requirements into scalable data solutions.

Cloud & Big Data

• Strong experience with AWS, including Redshift, Glue, and exposure to MLOps concepts.
• Familiarity with Apache Spark, Hadoop, and modern data lake architectures.

Data Analytics

• Experience preparing and modeling data for analytics, reporting, and data visualization
• Strong analytical and problem-solving skills, with a data-driven mindset.
• Ability to derive insights from data and communicate findings effectively.

Nice to Have

• Additional programming languages: Java, JavaScript.
• Experience with AI/ML workflows (e.g., AWS SageMaker).
• Knowledge of data security, encryption, compression, and privacy best practices.
• Familiarity with data governance frameworks, metadata management, and data quality controls.

Qualifications

• Typically 4–6+ years of relevant experience in data engineering, analytics, or related fields.
• Post-secondary degree in a related discipline or an equivalent combination of education and experience.
• Demonstrated ability to work independently on complex initiatives while collaborating effectively across teams.

The above represents BMO Financial Group’s pay range and type.

Salaries will vary based on factors such as location, skills, experience, education, and qualifications for the role, and may include a commission structure. Salaries for part-time roles will be pro-rated based on number of hours regularly worked. For commission roles, the salary listed above represents BMO Financial Group’s expected target for the first year in this position.

BMO Financial Group’s total compensation package will vary based on the pay type of the position and may include performance-based incentives, discretionary bonuses, as well as other perks and rewards. BMO also offers health insurance, tuition reimbursement, accident and life insurance, and retirement savings plans. To view more details of our benefits, please visit: https://jobs.bmo.com/global/en/Total-Rewards

About Us

At BMO we are driven by a shared Purpose: Boldly Grow the Good in business and life. It calls on us to create lasting, positive change for our customers, our communities and our people. By working together, innovating and pushing boundaries, we transform lives and businesses, and power economic growth around the world.

As a member of the BMO team you are valued, respected and heard, and you have more ways to grow and make an impact. We strive to help you make an impact from day one – for yourself and our customers. We’ll support you with the tools and resources you need to reach new milestones, as you help our customers reach theirs. From in-depth training and coaching, to manager support and network-building opportunities, we’ll help you gain valuable experience, and broaden your skillset.

To find out more visit us at https://jobs.bmo.com/ca/en.

BMO is committed to an inclusive, equitable and accessible workplace. By learning from each other’s differences, we gain strength through our people and our perspectives. Accommodations are available on request for candidates taking part in all aspects of the selection process. To request accommodation, please contact your recruiter.

Note to Recruiters: BMO does not accept unsolicited resumes from any source other than directly from a candidate. Any unsolicited resumes sent to BMO, directly or indirectly, will be considered BMO property. BMO will not pay a fee for any placement resulting from the receipt of an unsolicited resume. A recruiting agency must first have a valid, written and fully executed agency agreement contract for service to submit resumes.