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TPM- Data Engineering

  • Toronto, ON, Canada

Full-time

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Job details

Job type
Full-time
Posting language
English
Posted

Original job description

Technical Program Manager (TPM) – Databricks Platform


Role Overview

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.

Key Responsibilities

Program Leadership

  • 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.

Databricks Platform Ownership

  • 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.

Technical Strategy & Execution

  • 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

Stakeholder & Business Alignment

  • 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.

Delivery Excellence

  • Define and track KPIs, SLAs, and program success metrics.
  • Identify and mitigate risks, dependencies, and bottlenecks.
  • Ensure adherence to Agile / Scrum / SAFe methodologies.

Data Governance & Security

  • Ensure compliance with:
    • Data governance policies
    • Security and privacy regulations
  • Implement best practices for:
    • Data lineage
    • Data quality
    • Access controls

Skills & Qualifications

Mandatory Skills

  • 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.

Technical Expertise

  • Data Engineering concepts:
    • Data modeling, ETL/ELT, pipelines
  • Real-time streaming (Kafka / Event Hub)
  • CI/CD for data pipelines
  • DataOps / MLOps frameworks

Program Management Skills

  • Strong experience in:
    • Agile / Scrum / SAFe frameworks
    • Program governance and reporting
  • Excellent stakeholder management skills, including C-level engagement.

More about this job

Responsibilities

Lead the end-to-end execution of large-scale data and AI transformation programs using Databricks Lakehouse architecture. Coordinate cross-functional teams to design and implement scalable data platforms while aligning technical execution with business requirements.

Requirements

Requires over 10 years of technology experience with at least 5 years in program management and deep expertise in Databricks and Spark. Candidates must be proficient in cloud platforms and Agile methodologies to deliver enterprise-grade data solutions.

Skills

  • Databricks
  • Apache Spark
  • PySpark
  • SQL
  • Delta Lake
  • Azure
  • AWS
  • GCP
  • Program Management
  • Agile
  • Scrum
  • SAFe
  • Data Engineering
  • ETL/ELT
  • Stakeholder Management
  • Data Governance

Visa sponsorship

Not detected in the job text

Categories

  • Data & Analytics
  • Technology
  • Management & Leadership
  • Software
  • Engineering

Keywords

  • Databricks
  • Lakehouse
  • Delta Lake
  • Apache Spark
  • PySpark
  • SQL
  • Azure Databricks
  • AWS Databricks
  • GCP
  • Medallion Architecture
  • ETL
  • ELT
  • Azure Data Factory
  • Airflow
  • Power BI
  • Tableau
  • MLflow
  • Feature Store
  • Kafka
  • Event Hub
  • CI/CD
  • DataOps
  • MLOps
  • Agile
  • Scrum
  • SAFe
  • Data Governance
  • Data Lineage
  • Data Modeling
  • IT Services

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