Associate Director - Data Engineering

WHO WE ARE:

Zinnia is the leading technology platform for accelerating life and annuities growth. With innovative enterprise solutions and data insights, Zinnia simplifies the experience of buying, selling, and administering insurance products. All of which enables more people to protect their financial futures. Our success is driven by a commitment to three core values: be bold, team up, deliver value – and that we do. Zinnia has over $180 billion in assets under administration, serves 100+ carrier clients, 2500 distributors and partners, and over 2 million policyholders.

WHO YOU ARE:

As the Assoc Director of Data Engineering, you will assume day-to-day technical leadership and people leadership responsibilities for a couple of our core business lines. You will oversee the planning, development, and maintenance of our data platform. Your role will have a high degree of collaboration with cross-functional stakeholders to determine the optimal data-driven outcomes. Your role will be pivotal in ensuring the reliability, scalability, and efficiency of our data systems, enabling data-driven decision- making across the organization. 

WHAT YOU’LL DO:

• Oversee the technological choices and implementation of data pipelines and warehousing strategies
• Design data sets that are simple, maintainable, and enable Data Analysts, Data Scientists, and stakeholders to work efficiently with data
• Lead cross-organizational efforts aimed at automating our data processes and data-as-a-service capabilities
• Advocate for and implement technical best practices throughout the data organization to ensure high-quality outcomes
• Mentor data team members fostering a culture of learning and continuous improvement
• Partner with other leaders to bring innovative concepts to reality and design data models for downstream data maximization
• Ensure reliability in data pipelines and enforce data governance, security, and protection of customer information while balancing technical debt.
• Evaluate and champion new engineering tools that enhance efficiency and scalability within the team.

WHAT YOU’LL NEED:

• A Bachelor/Master’s Degree in Computer Science or related field with 10+ years of experience in Data Engineering.
• Extensive experience with data engineering techniques, including proficiency in Python and SQL.
• You are acquainted with designing custom Machine Learning (ML) pipelines that integrate into production environments that are customer facing.
• You have experience working on product teams but also collaborating with other data science team members.
• You can communicate with a team and articulate ideas to both team members and non-technical stakeholders.
• Strong Working knowledge of Airflow, dbt, Jira, Git, and Data Warehousing tools (BigQuery, Snowflake)
• Experience in tools such as GitHub Actions, Terraform, containers
• Proven track record in leading data engineering teams, mentoring staff, and promoting a culture of learning and teaching.
• Demonstrated ability to take risks when seeking novel solutions to complex problems and to persist in the face of roadblocks.

Technologies you will use & must be well-versed with:

• Python for data pipelining and automation
• Airbyte and Airflow for ETL purposes.
• GCP or AWS platforms utilizing tools like Terraform, Container services (GKE/EKS), Cloud Functions / Lambda, BigQuery/Snowflake
• dbt for data modeling.
• PowerBI for data visualization and consumer-facing dashboards.

WHAT’S IN IT FOR YOU?

At Zinnia, you collaborate with smart, creative professionals who are dedicated to delivering cutting-edge technologies, deeper data insights, and enhanced services to transform how insurance is done. Visit our website at www.zinnia.com for more information. Apply by completing the online application on the careers section of our website. We are an Equal Opportunity employer committed to a diverse workforce. We do not discriminate based on race, religion, colour, national origin, gender, sexual orientation, age, marital status, veteran status, or disability

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