Data Engineer I
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Key skills for this role
About the Role
TD is seeking a Data Engineer I to join the Data Strategy & Implementation team. You will design, build, and debug Databricks notebooks and ETL pipelines, onboard new data sources, and ensure reliable data flow for analytics, reporting, and AI models.
Key Skills for This Role
Responsibilities
- Independently design, build, and debug Databricks notebooks and ETL pipelines that ingest and transform data from a wide range of sources
- Onboard new data sources into the ingestion framework end to end
- Establish secure connectivity to source systems by working through networking fundamentals and provisioning access
- Write secure, high performance ETL code using Python, Spark, and PySpark on Azure Data Factory, Azure Databricks, ADLS, and Delta Lake
- Own the reliability of pipelines, troubleshoot issues, tune performance, and keep data flowing accurately
- Collaborate with source owners, platform, networking, and partner teams to deliver ingestion and data product work
Requirements
- Hands on experience building and debugging data pipelines on Azure Databricks, Azure Data Factory, ADLS, and Delta Lake
- Strong programming skills in Python, plus practical experience with Spark and PySpark for large scale data processing
- Solid grounding in relational databases and SQL
- Working knowledge of networking fundamentals
- Comfort with API basics and common authentication patterns
Full Job Posting
Purpose
- We are the Data Strategy & Implementation team. We own the pipelines that bring data into our platform and the curated data products that flow back out to our partners.
People
- You will join a close knit group of data engineers and analysts who take real ownership of what they build.
Presence
- We work in a hybrid model, combining focused remote days with regular in person collaboration.
Why This Role Matters
- Everything downstream depends on data arriving cleanly, securely, and on time. As a Data Engineer, you are at the front of that chain.
What You'll Do
- Independently design, build, and debug Databricks notebooks and ETL pipelines.
- Onboard new data sources into our ingestion framework end to end.
- Establish secure connectivity to source systems.
- Write secure, high performance ETL code using Python, Spark, and PySpark on Azure.
- Own the reliability of your pipelines.
- Collaborate with source owners, platform, networking, and partner teams.
Where You'll Work
- This is a hybrid role. You will spend part of your week working remotely and part collaborating in person.
Experience and/or Education
- Hands on experience building and debugging data pipelines on Azure Databricks, Azure Data Factory, ADLS, and Delta Lake.
- Strong programming skills in Python, plus practical experience with Spark and PySpark.
- Solid grounding in relational databases and SQL.
- Working knowledge of networking fundamentals.
- Comfort with API basics and common authentication patterns.
Preferred Qualifications
- Experience onboarding new sources into an established ingestion framework.
- Familiarity with building or exposing curated data products.
- Exposure to data governance, data quality, or data lifecycle management practices.
- Experience using AI assisted development tools.
- A track record of strong end to end ownership and mentoring.
Why Join Us
- You will own meaningful problems from end to end and see your pipelines power analytics, reporting, AI, and compliance work.
Who We Are
- TD is one of the world's leading global financial institutions and the fifth largest bank in North America.
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