At a Glance
- Tasks: Design and maintain data pipelines while collaborating with teams to drive data innovation.
- Company: Join a leading financial services firm focused on data analytics.
- Benefits: Hybrid work model, competitive salary, and opportunities for professional growth.
- Other info: Dynamic environment with a focus on data governance and advanced analytics.
- Why this job: Be part of a high-impact team transforming the wealth tech space.
- Qualifications: 5-7 years in data engineering with strong SQL and cloud experience.
The predicted salary is between 121500 - 148500 $ per year.
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 a 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 Management / Asset Management / Capital Markets) is nice to have.
Screening Questions:
- How proficient are you with programming languages and tools for data engineering tasks (e.g., SQL, Python, Airflow, Terraform)? How many years?
- Can you describe your experience designing, building, and maintaining ETL/ELT pipelines? Which tools and technologies did you use?
- Have you worked directly with analysts or business stakeholders to translate business needs into technical data solutions? Can you share an example?
- What is your experience designing data architectures on AWS using services like Glue, S3, Lambda, and Redshift or Snowflake?
- How do you ensure data quality, observability, and lineage in your pipelines? What tools or practices have you implemented?
- Have you participated in or led a cloud data migration project? What was your role and what challenges did you face?
- Have you worked with CI/CD pipelines for data deployments or infrastructure? What tools did you use and how did you manage rollouts?
- 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 the above screening questions to: sasha@talenttohire.com
For more positions, visit: Talent To Hire Inc. uses Workwolf’s AI-enabled tools to sort and screen applications based on job-related criteria. All hiring decisions involve human review.
Hybrid Data Engineer in Toronto employer: Talent To Hire Inc.
At Talent To Hire Inc., we pride ourselves on being an exceptional employer that fosters a culture of innovation and continuous improvement. As a Chief Technology Officer, you will have the opportunity to lead transformative AI initiatives in a dynamic environment, while benefiting from our commitment to employee growth and development. Located in a vibrant tech hub, we offer competitive compensation, flexible work arrangements, and a collaborative atmosphere that empowers you to make a meaningful impact.
