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VP, Data Engineering

With a company culture rooted in collaboration, expertise and innovation, we aim to promote progress and inspire our clients, employees, investors and communities to achieve their greatest potential. Our work is the catalyst that helps others achieve their goals. In short, We Enable Possibility℠.

The Position

Strategic Analytics is a key team at Arch that has established itself as a driving force in how the business is run. This is achieved through the implementation of real-time analytic solutions that improve profitability and growth. Our track record is 100% adoption of our tools and services. Data is critical to our mission. We create best-in-class data solutions from internal and external sources by leveraging a diverse set of cutting-edge tools.

As VP, Data Engineering, you will lead the development of complex data pipelines that that put analytics at the heart of decision-making. You will work closely with other members of the Strategic Analytics team on high-profile analytics projects that drive business strategies. As a key member of the team, you will extend our capacity to deliver and push the team forward.

Job Responsibilities

  • Work with strategic partners to solve business problems by directing the development of best-in-class data solutions.
  • Collaborate on high-profile analytics projects to drive business strategies.
  • Direct operations and resources to deliver data solutions.
  • Build strong partnerships across the organization to support data goals.
  • Develop and mentor employees to ensure top-tier data assets.
  • Proactively identify and resolve challenges with creative solutions. 
  • Communicate project progress to senior stakeholders.
  • Contribute to and promote the adoption of evolving best practices.
  • Prioritize competing priorities across portfolios and resources.
  • Continuously advance team capabilities and workflows.

Required Skills/Experience

  • Exceptional collaboration and relationship-building skills.
  • Ability to handle ambiguous concepts and break down complex problems.
  • Demonstrated experience building data structures for analytics in an insurance setting.
  • Strong problem-solving and critical thinking skills.
  • Effective communication to various audiences.
  • Flexibility to meet changing requirements and priorities.

Desired Skills/Experience

  • P&C insurance data engineering experience
  • Experience with cloud technologies like Snowflake and Databricks is a plus.
  • Knowledge of the MLOps framework.
  • 10+ years of data engineering experience.
  • 5+ years of project management experience.

Education

  • College degree in Computer Science, Engineering, Data Analytics, or equivalent

For individuals assigned or hired to work in the location(s) indicated below, the base salary range is provided. Range is as of the time of posting. Position is incentive eligible.

$200,00 - $270,500/year

  • Total individual compensation (base salary, short & long-term incentives) offered will take into account a number of factors including but not limited to geographic location, scope & responsibilities of the role, qualifications, talent availability & specialization as well as business needs. The above pay range may be modified in the future.

Click here to learn more on available benefits.

Do you like solving complex business problems, working with talented colleagues and have an innovative mindset? Arch may be a great fit for you. If this job isn’t the right fit but you’re interested in working for Arch, create a job alert! Simply create an account and opt in to receive emails when we have job openings that meet your criteria. Join our talent community to share your preferences directly with Arch’s Talent Acquisition team.

10200 Arch Capital Services LLC

Average salary estimate

$235250 / YEARLY (est.)
min
max
$200000K
$270500K

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 VP, Data Engineering, Archgroup

If you're looking for an opportunity where you can truly make an impact, Arch Capital Services LLC is seeking a passionate VP, Data Engineering to lead our strategic analytics efforts in Hartford, CT. Our company thrives on collaboration, innovation, and expertise, helping our clients, employees, and communities unlock their fullest potential. As the VP of Data Engineering, you'll spearhead the development of complex data pipelines that are central to decision-making processes and the overall business strategy. You'll collaborate closely with our dynamic Strategic Analytics team on high-profile projects aimed at driving business growth and profitability. One of your top priorities will be to build strong partnerships across the organization to support our data goals. You'll also have the freedom to identify challenges creatively and develop mentorship pathways for your team to ensure top-tier data assets are consistently delivered. With our rich analytics environment where 100% adoption of tools and services is the norm, your efforts will directly contribute to our mission of enabling possibility. We believe data holds the key to progress, and you're just the right leader to unlock it. If you have over a decade of data engineering experience and can manage competing priorities while flexibly adapting to change, we want to hear from you. Let's collaborate and create innovative data solutions that make a difference!

Frequently Asked Questions (FAQs) for VP, Data Engineering Role at Archgroup
What are the key responsibilities of the VP, Data Engineering at Arch Capital Services LLC?

As the VP, Data Engineering at Arch Capital Services LLC, you'll be responsible for directing the development of best-in-class data solutions, collaborating on strategic analytics projects, and managing operations to ensure efficient data delivery. You'll also focus on building robust partnerships across the organization and mentoring your team to maintain high-quality data assets.

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What qualifications are required for the VP, Data Engineering position at Arch Capital Services LLC?

To qualify for the VP, Data Engineering role at Arch Capital Services LLC, you should have a college degree in Computer Science, Engineering, or Data Analytics along with over 10 years of data engineering experience and at least 5 years in project management. Experience in the P&C insurance sector and familiarity with cloud technologies like Snowflake or Databricks would be advantageous.

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What skills are essential for a successful VP, Data Engineering at Arch Capital Services LLC?

Essential skills for the VP, Data Engineering role at Arch Capital Services LLC include exceptional collaboration and relationship-building abilities, strong problem-solving skills, and effective communication across varying audiences. A background in building data structures for analytics, particularly in the insurance domain, will be critical to achieving success.

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What kind of projects will the VP, Data Engineering lead at Arch Capital Services LLC?

As VP, Data Engineering at Arch Capital Services LLC, you'll lead high-profile analytics projects that drive business strategies. These projects will include developing complex data pipelines essential for real-time analytics that aim to improve profitability and growth within the organization.

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What does the company culture look like for the VP, Data Engineering at Arch Capital Services LLC?

The company culture at Arch Capital Services LLC is rooted in collaboration, expertise, and innovation. As a VP, Data Engineering, you can expect to work in an inspiring environment that promotes progress, enabling employees to achieve their greatest potential while driving impactful analytics solutions.

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Common Interview Questions for VP, Data Engineering
Can you describe your experience with building data structures for analytics?

When answering this question, focus on specific projects where you developed data structures that significantly impacted business decisions. Highlight your role, the technologies used, and how these structures improved analytical outcomes.

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How do you prioritize competing data project demands?

The key to answering this question is discussing your methodology for prioritization, such as using data-driven decision-making, stakeholder input, and long-term strategic goals. Provide an example where you effectively balanced multiple demands while achieving successful outcomes.

Join Rise to see the full answer
What strategies do you use to mentor your team in data engineering?

Share your approach to mentorship, such as setting up regular feedback sessions, encouraging knowledge sharing, and involving team members in strategic discussions to ensure their growth aligns with organizational goals.

Join Rise to see the full answer
Describe a time where you encountered a major data challenge and how you solved it.

When presenting your solution to a data challenge, categorize your answer into the problem, your assessment and actions taken, and the final outcome. Keep it structured and focus on your creative and analytical thinking during the process.

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What tools and technologies are you most proficient in for data engineering?

In your response, list relevant tools, focusing on those crucial to the role at Arch Capital Services LLC, such as cloud platforms (e.g., Snowflake and Databricks) and any machine learning frameworks. Provide context on how you've applied them in previous projects.

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How do you ensure effective communication with diverse stakeholders?

Discuss the methods you use to tailor your communication style according to the audience, such as using clear visuals for technical details when speaking to non-technical stakeholders or diving deep into technical specifics with data teams.

Join Rise to see the full answer
What is your experience with the MLOps framework?

Speak about any hands-on experience you have with MLOps, emphasizing the significance of maintaining and scaling machine learning models as part of a data engineering workflow. Provide examples of how you have integrated MLOps into your data strategies.

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How do you handle ambiguous concepts in data projects?

Explain your approach by mentioning processes such as breaking down complex problems into manageable parts, prototyping potential solutions, and continually engaging with team members for clarity and direction.

Join Rise to see the full answer
What is your approach to adopting evolving best practices in data engineering?

Illustrate your commitment to professional development, such as attending workshops, participating in webinars, or engaging with industry forums to stay updated. Mention how you have applied new best practices to enhance your team's performance.

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How do you measure the success of data engineering initiatives?

Prepare to discuss the metrics you consider critical for evaluating data engineering outcomes, such as accuracy, speed, and impact on business decisions. Provide specific instances in which you measured success and adapted strategies based on results.

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EMPLOYMENT TYPE
Full-time, on-site
DATE POSTED
April 9, 2025

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