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Director of Data Strategy

About CareScout Services:

Join us on a mission to simplify and dignify the aging experience. We are the children, siblings, neighbors, and friends of those navigating the fragmented and confusing system of long-term care. Our team is ferociously curious and relentless in our pursuit of a better system – and we are deeply committed to a sense of belonging for all, in all phases of life.

We’re creating a new experience for care seekers and their families, bringing together long-term care options, resources, education, and human support into one place. We work hard, we have fun, we care about each other, and we share the mission. If this sounds like a place where you could thrive, join us!

CareScout is a division of Genworth Financial, Inc, a Fortune 500 provider of products, services and solutions that help families address the financial challenges of aging.

Job Summary:
The Director of Data Strategy will lead the development and execution of our data strategy, with a strong focus on building and leveraging a robust data lake on the Azure platform. This role will be instrumental in enabling advanced analytics, driving marketing integrations, and fostering a data-driven culture. The ideal candidate will have deep technical expertise in Data Engineering and a proven track record of delivering impactful data solutions that enhance marketing effectiveness and overall business performance.

Responsibilities:
Strategic Data Leadership:

  • Develop and implement a comprehensive data strategy aligned with business objectives

  • Identify opportunities to leverage data for competitive advantage, particularly in marketing and customer engagement.

  • Provide thought leadership on data trends, technologies, and best practices..

  • Develop and implement an enterprise data model & data dictionary to standardize our reporting needs.

  • Data Lake Development and Management:

  • Design, build, and maintain a scalable and secure data lake on Azure.

  • Design and build scalable ETL pipelines, establish data ingestion, transformation, and storage patterns.

  • Architect data warehouse schema (Star, Snowflake, Galaxy)

  • Optimize data lake performance and ensure data quality and integrity.

  • Establish balancing and reconciliation queries to ensure Data warehouse is stable after failures, numbers and records match to expectations to ensure quality, consistency and availability

  • Enabling the business to leverage Artificial Intelligence and Machine Learning:

  • Work with the product managers, and the business stakeholders to identify opportunities to use AI/ML solutions.

  • Stay abreast on trends in AI/ML

  • Ensure data availability and quality

  • Establish data governance for ML – Define & Implement policies and procedures that ensure quality, consistency and security for ML models

  • Manage data pipelines for ML

  • Address data privacy and ethical considerations

  • Collaborate with data scientists and engineers

  • Establish ML model lifecycle management – develop process for model development, deployment, monitoring and maintenance.

  • Enable model operationalization (MLOps)- adopt MLOps practices to manage process

  • Measure and monitor ML model performance: Establish metrics and processes for measuring and monitoring the performance of ML models in production


Marketing Data Integration and Activation:

  • Lead the integration of marketing data from various sources (CRM, marketing automation platforms, and other operational systems) into the data lake.

  • Enable the use of data lake data for targeted marketing campaigns, customer segmentation, and personalized experiences.

  • Collaborate with marketing teams to develop and implement data-driven marketing strategies.

  • Oversee the activation of data to marketing platforms, and ensure a smooth flow of information.

  • Data Governance and Compliance:

  • Establish and enforce data governance policies and procedures, ensuring compliance with relevant data privacy regulations.

  • Implement data security measures to protect sensitive data within the Azure environment.

  • Define and manage data access controls and permissions.


Data Analytics and Insights:

  • Partner with analytics teams to leverage the data lake for advanced analytics, reporting, and business intelligence.

  • Promote the use of data analytics to drive informed decision-making across the organization.

  • Project Execution

  • Develop project plans and estimates

  • Develop milestones, and identify risks

  • Establish project control and communicate progress, risks and mitigation plans


Team Leadership and Collaboration:

  • Build and lead a high-performing data strategy team with expertise in Azure data services.

  • Hire coach and mentor staff and contracting team members

  • Collaborate with cross-functional teams, including product management, marketing, operations, sales, and analytics, to achieve data-related objectives.

  • Manage relationships with vendors.

  • Plan and manage budget


Qualifications:

  • Bachelor's degree in computer science, data science, or a related field (Master's degree preferred).

  • Minimum of 10 years of experience in data strategy, data engineering, or a related field, with a focus on Azure data services.

  • Proven experience building and managing data lakes on the Azure platform.

  • Strong expertise in Data Lake technologies such as Databricks or Azure Synapse, or Snowflake.

  • Experience with marketing data integration and activation.

  • Strong understanding of data governance, data security, and compliance principles.

  • Excellent leadership, communication, and interpersonal skills.

  • Strong analytical and problem-solving abilities.

  • Experience in managing globally distributed teams of data engineers as staff and contractors


Desired Skills:

  • Experience with Databricks or Snowflake or Azure Syanpse/Fabric

  • Experience in Extract Transform and Load (ETL) tools like Fivetran or others like Azure Data Factory, AWS Glue, Apache airflow

  • Hands-on experience in architecting data warehouse using Star, Snowflake or Galaxy schema

  • Proficiency with at least one cloud platform (Azure, AWS, or GCP)

  • Experience in data security

  • Strong understanding of relational databases (MySQL, Postgress, SQL Server, MongoDB)

  • Advanced SQL skills

  • Experience in data dictionary, data quality and lineage tools

  • Experience in machine learning frameworks: Pytorch, MLFlow, and or Tensorflow

  • Experience with marketing automation platforms (e.g., Iterable, Dynamic 360).

  • Experience with CRM platforms (e.g. Dynamics 365).

  • Experience with API integrations.

  • Experience with data visualization tools like Power BI or Tableau

  • Experience with Data visualizations tools such as Power BI.

  • Understanding of ML concepts and algorithms (supervised learning, unsupervised learning, deep learning)

  • Understanding of ML Ops best practices

  • Understanding of API concepts with experience in integrating data from diverse sources

  • Experience in Metadata Management, and Data Modeling

WHY CARESCOUT SERVICES?
• We have a real impact on the lives of the people we serve
• We work on challenging and rewarding projects
• We give back to the communities where we live
• We offer competitive benefits including:
o Medical, Dental, Vision, Flexible Spending Account options beginning your first day  
o Generous Choice Time Off your first full year
o 12 Paid Holidays
o 40 hours of volunteer time off
o 401k Account with matching contributions
o Tuition Reimbursement and Student Loan Repayment
o Paid Family Leave
o Child Care Subsidy Program

Average salary estimate

$175000 / YEARLY (est.)
min
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$150000K
$200000K

If an employer mentions a salary or salary range on their job, we display it as an "Employer Estimate". If a job has no salary data, Rise displays an estimate if available.

What You Should Know About Director of Data Strategy, GNW

Are you passionate about data and its power to impact businesses and lives? Carescout Services in New York, New York, is looking for a Director of Data Strategy who can lead and innovate in shaping our data landscape. Our mission is to transform the way we navigate the challenges of aging, and as the Director of Data Strategy, you will be at the forefront of creating solutions that empower families to make informed decisions about long-term care. You'll develop and execute a comprehensive data strategy, with an emphasis on building a robust data lake on the Azure platform, enabling advanced analytics and driving marketing integrations. Your expertise in data engineering and leadership will ensure we leverage data for competitive advantage. You'll be responsible for managing a high-performing team, overseeing the design and maintenance of data architecture, and collaborating with cross-functional teams to integrate marketing data seamlessly into our operations. This role goes beyond technical capabilities; it involves fostering a data-driven culture and ensuring that data governance policies are in place. At Carescout, we value curiosity, cooperation, and a sense of belonging, and if you believe that you can contribute to a cause that genuinely makes a difference in people's lives, we would love to hear from you!

Frequently Asked Questions (FAQs) for Director of Data Strategy Role at GNW
What are the main responsibilities of the Director of Data Strategy at Carescout Services?

The Director of Data Strategy at Carescout Services is responsible for leading data strategy development, managing data lake implementation on the Azure platform, and driving marketing integrations to enhance customer engagement. This includes establishing data governance policies, optimizing data quality, and collaborating with cross-functional teams to promote a data-driven culture.

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What qualifications are required for the Director of Data Strategy position at Carescout?

Candidates for the Director of Data Strategy role at Carescout should have a bachelor's degree in computer science or a related field, with at least 10 years of experience in data strategy or data engineering. A strong background in Azure data services, data governance, and marketing data integration is crucial for success in this position.

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How does Carescout Services leverage data for business improvements?

Carescout Services utilizes data to identify competitive advantages in marketing and customer engagement, improving efficiency and effectiveness. The Director of Data Strategy will lead efforts to develop actionable insights through advanced analytics and ensure that data-driven strategies are operationalized across the organization.

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What technical skills are essential for the Director of Data Strategy role at Carescout?

Essential technical skills for the Director of Data Strategy at Carescout include expertise in Azure data services, data lake technologies such as Databricks or Snowflake, and proficiency in ETL tools. Familiarity with advanced analytics, machine learning frameworks, and data visualization tools is also beneficial.

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What is the significance of data governance in the Director of Data Strategy's role at Carescout?

Data governance plays a vital role in the Director of Data Strategy's responsibilities at Carescout. It ensures data quality, security, compliance with regulations, and creates a structured framework for managing data assets effectively, establishing principles that guide data usage throughout the organization.

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Common Interview Questions for Director of Data Strategy
Can you explain your experience with building and managing data lakes?

In your response, highlight specific projects where you implemented a data lake. Discuss the technologies you used, such as Azure or Snowflake, and how you ensured data quality and integrity throughout the process. Be prepared to share challenges faced and solutions implemented.

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How do you approach developing a data strategy aligned with business objectives?

Outline your strategy development process. Discuss how you conduct stakeholder interviews to understand business goals, assess existing data capabilities, and identify opportunities for leveraging data. Use examples that showcase your ability to connect data strategies with organizational needs.

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What methods do you use for ensuring data privacy and security?

Talk about the policies you have implemented in previous roles to ensure data privacy and security. Discuss compliance with relevant regulations, such as GDPR or HIPAA, and how you establish access controls and monitor data usage within organizations.

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Describe a time when you had to work with cross-functional teams. How did you ensure successful collaboration?

Share specific instances highlighting the importance of communication and setting clear expectations. Explain how you navigated different team dynamics and ensured all parties were aligned toward common goals, focusing on data-driven projects.

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What is your experience with machine learning and AI integration in data strategy?

Discuss any hands-on experience you have with machine learning frameworks like TensorFlow or PyTorch. Share examples of how you’ve identified opportunities to apply AI/ML to business problems and the impact it had on business operations or decision-making.

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How do you measure the effectiveness of a data strategy?

Explain the key performance indicators (KPIs) you track to evaluate the success of data initiatives. Discuss how you analyze these metrics to make informed decisions about future strategies and improvements.

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What challenges have you faced when designing ETL processes, and how did you overcome them?

Provide an example of a specific challenge related to ETL development you faced in previous roles. Describe the steps you took to troubleshoot issues and how your proactive approach led to a successful resolution.

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Can you give an example of a project where analytics drove business decisions?

Share a project where analytics were instrumental in arriving at a critical business decision. This could include data processes you initiated, insights gained, and how those insights led to tangible results for the organization.

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How do you ensure data quality throughout the organization?

Discuss your approach to establishing data governance policies and the practices you implement to monitor data quality. Highlight examples of tools and frameworks you’ve used.

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Why do you believe a data-driven culture is vital for organizations today?

Share your thoughts on the strategic importance of data in driving organizational success. Discuss how empowering employees with data insights can lead to better decision-making, innovation, and customer engagement.

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Full-time, on-site
DATE POSTED
March 29, 2025

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