TPM- Data Engineering

iLink Digital•Toronto, ON

About The Position

We are seeking an experienced Technical Program Manager (TPM) with strong expertise in Databricks and modern data platforms to lead and drive large-scale data & AI transformation programs. This role will work at the intersection of business, data engineering, and platform architecture, ensuring successful delivery of enterprise-grade data solutions on Databricks.

Requirements

10+ years in technology roles, with 5+ years in program management.
Strong hands-on or working knowledge of: Databricks (must-have), Apache Spark / PySpark / SQL, Delta Lake architecture.
Experience in cloud platforms: Azure (preferred), AWS, or GCP.
Proven experience delivering enterprise data platform programs.
Data Engineering concepts: Data modeling, ETL/ELT, pipelines.
Real-time streaming (Kafka / Event Hub).
CI/CD for data pipelines.
DataOps / MLOps frameworks.
Strong experience in: Agile / Scrum / SAFe frameworks, Program governance and reporting.
Excellent stakeholder management skills, including C-level engagement.

Responsibilities

Drive end-to-end execution of data platform programs built on Databricks (Lakehouse architecture).
Manage multiple cross-functional teams including data engineering, data science, DevOps, and BI teams.
Own program roadmap, delivery timelines, risk management, and stakeholder communication.
Establish governance frameworks for program delivery, quality, and performance tracking.
Lead design and implementation of Databricks-based data platforms (Azure Databricks / AWS Databricks / GCP).
Ensure best practices in: Delta Lake, Data pipelines (batch + streaming), Medallion architecture (Bronze, Silver, Gold layers).
Drive platform optimization including cost, performance, and scalability.
Collaborate with architects to define data architecture standards and patterns.
Oversee development of: ETL/ELT pipelines, Data ingestion frameworks, Data transformation and curation layers.
Ensure integration with ecosystem tools like: Azure Data Factory / Airflow, Power BI / Tableau, MLflow, Feature Store.
Act as a bridge between business leaders and engineering teams.
Translate business requirements into technical execution plans.
Provide leadership updates and executive reporting on program progress.
Define and track KPIs, SLAs, and program success metrics.
Identify and mitigate risks, dependencies, and bottlenecks.
Ensure adherence to Agile / Scrum / SAFe methodologies.
Ensure compliance with: Data governance policies, Security and privacy regulations.
Implement best practices for: Data lineage, Data quality, Access controls.