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Senior Manager, Data Engineering & Delivery (Pod Lead)

Definity Financial

Toronto

On-site

CAD 100,000 - 130,000

Full time

Today
Be an early applicant

Job summary

A leading financial services firm in Toronto seeks a Senior Manager to lead Data Engineering efforts. The role involves managing cross-functional teams, overseeing the end-to-end delivery of data products, and innovating within the data platform. Candidates should have extensive experience in Data Analysis and team leadership, with knowledge of Big Data systems and a relevant degree. This position offers an opportunity to shape data strategy in a collaborative environment.

Qualifications

  • 8+ years in Data warehouse, Big Data, and Data Analysis.
  • 4+ years in team management ideally in an agile environment.
  • Experience with P&C Insurance Data is a strong asset.

Responsibilities

  • Lead Data Pods comprising engineers, analysts, and data scientists.
  • Oversee data product lifecycle from ideation to delivery.
  • Partner with stakeholders to gather requirements and prioritize features.

Skills

Team management
Data analysis
Strategic mindset

Education

Bachelor's or Master's degree in Computer Science

Tools

Hadoop
BigQuery
Snowflake
Python
Databricks
Job description
Overview

We are seeking a dynamic and experienced Senior Manager to lead our Data Engineering efforts, specifically focusing on the end-to-end delivery of critical data products within dedicated Data Pods. As a key leader, you will be instrumental in shaping our data strategy, guiding a multidisciplinary team of data professionals, and ensuring the timely and high-quality delivery of data solutions that drive business value.

You will oversee the execution of our data product roadmap, fostering collaboration between your teams and business stakeholders to translate complex requirements into robust, scalable data products. This role is pivotal in ensuring our data platform evolves to meet the dynamic needs of the organization, with a strong emphasis on innovation and operational excellence.

What can you expect in this role?
  • Data Pod Leadership:
    • Lead and manage one or more Data Pods, which comprise a cross-functional team of data engineers, analysts, data scientists, and other required resources.
    • Foster a collaborative, inclusive, and high-performance culture within your pods, empowering team members and promoting continuous learning.
    • Oversee resource management, hiring, onboarding, and talent development within your teams.
    • Drive accountability for the quality, timeliness, and success of all data products delivered by your pods.
  • End-to-End Data Product Delivery:
    • Take full ownership of the data product lifecycle, from initial ideation and user story definition through development, testing, deployment, and ongoing maintenance.
    • Ensure the technical excellence of data solutions, including data ingestion, transformation, modeling, and consumption, adhering to best practices.
    • Champion the implementation of robust data quality frameworks and monitoring.
    • Manage the technical roadmap for your assigned data products, ensuring alignment with broader organizational data strategy.
  • Business Collaboration & Requirements Management:
    • Partner closely with business stakeholders to understand their needs, gather requirements, and translate them into actionable user stories and technical specifications.
    • Facilitate prioritization of features and initiatives with business leads and product owners, ensuring alignment with strategic objectives and OKRs.
    • Communicate effectively with stakeholders regarding project status, challenges, and roadmap updates, managing expectations proactively.
  • Technical Strategy & Innovation:
    • Contribute to the development and execution of the overall Cloud data platform strategy, vision, and framework.
    • Stay abreast of emerging Big Data technologies and methodologies, identifying opportunities to leverage new tools and techniques to enhance our data capabilities.
    • Drive innovation in data ingestion, curation, and consumption insights.
  • Stakeholder Management & Partnership:
    • Collaborate effectively with functional leads across Product, Design, Engineering, and Data & Insights to set strategic direction and achieve shared goals.
    • Represent the data engineering function in cross-organizational initiatives.
What do you bring to the role?
  • Experience:
    • 8+ years of progressive experience in Data warehouse, Big Data and Data Analysis domains.
    • 4+ years of proven experience in team management and people leadership, ideally within a distributed or agile environment.
    • Demonstrated experience leading cross-functional teams to deliver end-to-end data products.
    • Experience in defining and executing product roadmaps and prioritizing backlogs with business stakeholders.
    • Experience with P&C Insurance Data domain strong asset
  • Technical Skills:
    • Hands-on experience and deep knowledge of the Big data systems like Hadoop, BigQuery, Snowflake etc.
    • Proficiency with programming languages such as Python, and experience with Databricks, Dataflow, or other relevant ETL/ELT tools.
    • Familiarity with message queuing technologies like Kafka or Pub/Sub.
    • Experience with cloud computing platforms (Google Cloud Platform is a strong plus), distributed systems, and data warehousing/data lake concepts.
    • Understanding of operational tools and systems (e.g., Guidewire, Claims, Policy management systems, Call centers, ServiceNow).
  • Leadership & Soft Skills:
    • Exceptional problem-solving abilities with a knack for diving deep into complex issues and formulating pragmatic solutions.
    • Strong communication, collaboration, and influencing skills, with the ability to work effectively with global teams and diverse stakeholders.
    • A passion for building and nurturing high-performing, inclusive teams.
    • A strategic mindset with the ability to balance speed to market with robust, scalable solutions.
    • A strong understanding of data governance, data quality, and data privacy principles.
  • Education:
    • Bachelor's or Master's degree in Computer Science, Data Science, Mathematics, Engineering, or a related field.
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