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Intermediate Data Analyst Jobs in Toronto, ON (NOW HIRING)

StarTech.com

Data Analyst

Toronto, ON · On-site +1

Intermediate proficiency in Python or R * Experience or interest in AI tools and applications What Sets You Apart * Strong data cleaning, transformation, and analysis skills * Ability to synthesize ...

JLL

Senior Data Engineer

Toronto, ON · Remote

Lead complex technical problem-solving initiatives, root cause analysis, and strategic decision-making for critical data systems * Mentor junior and intermediate data engineers on advanced concepts ...

Alquemy

Intermediate Business Analyst

Toronto, ON · Hybrid

Our Client is seeking an Intermediate Business Analyst to join their team for an exciting ... Data & Regulatory Exposure: Practical experience working on projects tied to financial data ...

Wood Plc

Intermediate Accountant

Oakville, ON · On-site

Prepare input files and upload monthly financial and supplementary data to HFM. * Review ... Strong numerical and analytical skills, combined with a strong understanding of Microsoft Excel ...

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Intermediate Data Analyst information

What is an intermediate data analyst?

Intermediate Data Analysts are professionals who collect, process, and analyze data to help organizations make informed decisions. They possess solid analytical skills, working knowledge of data analysis tools, and the ability to interpret complex data sets. Typically, they have some experience beyond entry-level roles and can handle more advanced tasks such as building reports, creating dashboards, and supporting business strategies with data-driven insights. Their work often involves collaborating with other teams to identify trends and provide actionable recommendations.

How does an intermediate data analyst typically collaborate with other departments within an organization?

As an Intermediate Data Analyst, you'll frequently work alongside teams such as marketing, finance, operations, and IT to gather requirements, interpret data needs, and deliver actionable insights. You may be responsible for translating business questions into analytical tasks, sharing findings through presentations or dashboards, and supporting decision-making processes. Collaboration often involves participating in cross-functional meetings, clarifying data definitions, and ensuring that analysis aligns with organizational goals. Building strong relationships with stakeholders is key to understanding their challenges and ensuring your work has maximum impact.

What are the key skills and qualifications needed to thrive as an intermediate data analyst, and why are they important?

To thrive as an Intermediate Data Analyst, you need strong analytical skills, experience with data manipulation and statistical analysis, and a relevant degree such as in mathematics, statistics, or computer science. Proficiency in tools like SQL, Excel, Python or R, and familiarity with data visualization platforms such as Tableau or Power BI are typically required. Attention to detail, effective problem-solving, and clear communication skills help you translate complex data into actionable insights for stakeholders. These skills and qualities are crucial for delivering accurate analyses that drive informed business decisions.

Is it still worth it to become a data analyst in 2026?

Data analyst roles remain valuable in 2026 as organizations continue to rely on data-driven decision-making, with skills in SQL, Excel, and data visualization tools like Tableau or Power BI in demand. The role often requires strong analytical skills, familiarity with programming languages such as Python or R, and the ability to interpret complex data sets, making it a stable career choice for those with relevant skills. Continuous learning and certification can enhance job prospects in this evolving field.

What is intermediate level data analysis?

Intermediate data analysts perform more complex data analysis tasks than entry-level roles, including data cleaning, visualization, and basic statistical modeling using tools like Excel, SQL, or Python. They interpret data insights to support decision-making and often work with larger datasets and more advanced techniques than beginners.

What are the most commonly searched types of Data Analyst jobs in Toronto, ON?

The most popular types of Data Analyst jobs in Toronto, ON are:

What are popular job titles related to Intermediate Data Analyst jobs in Toronto, ON?

For Intermediate Data Analyst jobs in Toronto, ON, the most frequently searched job titles are:

What job categories do people searching Intermediate Data Analyst jobs in Toronto, ON look for?

The top searched job categories for Intermediate Data Analyst jobs in Toronto, ON are:

What cities near Toronto, ON are hiring for Intermediate Data Analyst jobs?

Cities near Toronto, ON with the most Intermediate Data Analyst job openings:

Intermediate Data Analyst jobs near you
Infographic showing various Intermediate Data Analyst job openings in Toronto, ON as of August 2026, with employment types broken down into 1% As Needed, 85% Full Time, 11% Part Time, and 3% Contract. Highlights an 84% Physical, 4% Hybrid, and 12% Remote job distribution.

Intermediate Data Engineer ( SQL, Databricks/ Snowflakes, DBT, Airflow)

Talent To Hire Inc.

Toronto, ON • Remote

Full-time

Re-posted 27 days ago

Job description

INTERMEDIATE DATA ENGINEER- Toronto ( 3 days downtown/Hybrid)

Our client is interviewing to onboard an Intermediate Data Engineer to join their Data & Analytics team . We are looking for an Intermediate Data Engineer with proven track record working within the Financial sector. You’ll help build and optimize scalable data pipelines, support data governance, and enable advanced analytics across the organization. Be part of a high-impact team driving data innovation in the wealth tech space.

What You’ll Do:

  • Design, build, and maintain robust ETL/ELT data pipelines.

  • Collaborate with analysts and business teams to translate needs into technical solutions.

  • Recommend scalable data architectures using AWS, Snowflake, and modern data stack tools.

  • Ensure data quality, observability, and governance across systems.

  • Support migration projects to cloud-based platforms.

What You’ll Bring:

  • 5-7 years of data engineering experience.

  • Must have Solid SQL and either Snowflake or Databricks,

  • DBT and/or Airflow

  • Experience with CI/CD, data lineage, and monitoring tools.

  • Financial services ( Wealth Mgmt. / Asset Mgmt./ Capital Markets) is Nice to have.

    Screening Questions ( If you are comfortable with answering below questions at ease, apply) :

    1-How proficient are you with programming languages and tools for data engineering tasks (e.g., SQL, Python, Airflow, Terraform)? how many years?

    2- Can you describe your experience designing, building, and maintaining ETL/ELT pipelines? Which tools and technologies did you use?

    3-Have you worked directly with analysts or business stakeholders to translate business needs into technical data solutions? Can you share an example?

    4-What is your experience designing data architectures on AWS using services like Glue, S3, Lambda, and Redshift or Snowflake?

    5-How do you ensure data quality, observability, and lineage in your pipelines? What tools or practices have you implemented?

    6-Have you participated in or led a cloud data migration project? What was your role and what challenges did you face?

    7- Have you worked with CI/CD pipelines for data deployments or infrastructure? What tools did you use and how did you manage rollouts?


    8-Do you have experience working in financial services or other regulated industries? If so, what types of data and systems were involved?

Send your resume and reply to above screening questions to : sasha@talenttohire.com

For more positions , visit: https://www.linkedin.com/company/talenttohire/jobs