Senior Data Solutions Analyst: Operational Data & Reporting team
WFA Digital Insight
As demand for data-driven insights continues to rise, with a 25% increase in data scientist roles in the past year, professionals with expertise in scalable data solutions are in high demand. Liberty Mutual Insurance's quest for a Senior Data Solutions Analyst reflects the growing need for professionals who can bridge the gap between data and business strategy. With the insurance industry leveraging data to personalize customer experiences, the role of a data solutions analyst has become pivotal. Candidates should be prepared to showcase their technical prowess, particularly in Excel, SQL, and Power BI, as well as their ability to communicate complex data insights to non-technical stakeholders. Before applying, candidates should consider how their skills align with the company's focus on leveraging data as a competitive differentiator.
Job Description
About the Role
The Senior Data Solutions Analyst position at Liberty Mutual Insurance is a pivotal role within the Operational Data & Reporting team, part of the USRM Data Office. This team is dedicated to ensuring that data serves as a competitive differentiator for the enterprise, focusing on strategic data product visions, data governance, and the development of best-in-class data and reporting solutions. The ideal candidate will have a strong technical aptitude, with expertise in data manipulation, data wrangling, and reporting tools, including Excel, SQL, and Power BI.Day-to-day, the Senior Data Solutions Analyst will design and develop scalable data solutions with a focus on reusability, enabling effective self-service data consumption. This involves working independently on prototyping and developing data solutions that meet the needs of the organization and its business customers. A key aspect of this role is staying up to date with advancements in data engineering, evaluating new tools, and recommending their adoption where appropriate.
The role also involves collaboration with various stakeholders, including technical and non-technical team members, to ensure that data solutions are aligned with business objectives and customer needs. Given the remote nature of the position, strong communication and project management skills are essential to succeed in this role.
What You Will Do
- Design and develop scalable data solutions with a focus on reusability, enabling effective self-service data consumption.
- Work independently on prototyping and developing data solutions that meet the needs of the organization and its business customers.
- Stay up to date with advancements in data engineering, evaluate new tools, and recommend their adoption where appropriate.
- Identify opportunities to apply General AI for data discovery, lineage summarization, automated documentation, query generation, and developer productivity.
- Develop proof-of-concept solutions utilizing advanced understanding of multiple coding languages to meet technical and business requirements.
- Perform iterative solution testing to ensure specifications are met.
- Strive to become a technical leader and mentor for the team, providing assistance and guidance to junior team members.
- Optimize and tune data infrastructure for performance, scalability, reliability, and cost-efficiency.
- Prioritize efforts based on customer value and set expectations for deliverables of high complexity.
- Ensure data solutions include activities and deliverables required to achieve high data quality.
- Display a strong understanding of complex, multi-tier, multi-platform systems, applying principles of metadata, lineage, business definitions, compliance, and data security to project work.
What We Are Looking For
- Strong technical aptitude with data manipulation, data wrangling, and reporting tools (SQL, Power BI, SAS, Python, cloud computing: AWS and Snowflake).
- 3+ years of experience building production data pipelines, data solutions, and Power BI Dashboards.
- Hands-on experience with data quality testing frameworks and practices, and experience implementing automated data tests and validation.
- Excellent communication skills and the ability to work with technical and non-technical stakeholders.
- 3-5+ years of experience in coding for data management, data warehousing, or other data environments, including ETL and scripting languages (Python).
- 3-5+ years of experience with top quadrant Business Intelligence tools.
- Demonstrated technical knowledge and skills in coding languages and business intelligence tools (e.g., SQL, Power BI, SAS, Python) and an interest in expanding knowledge in this space.
- Strong analytical, strategic, project management, decision-making, and problem-solving skills.
- Direct Distribution domain knowledge is preferred but not required.
- A comprehensive understanding of new technologies as needed to progress initiatives and the ability to adapt.
- Ability to describe value and support the prioritization of data solutions.
- Ability to organize and address customer pain points.
Nice to Have
- Experience with cloud-based data platforms, such as AWS or Snowflake.
- Knowledge of data governance and compliance regulations.
- Familiarity with agile development methodologies.
- Certification in data science or a related field.
Benefits and Perks
- Competitive salary.
- Comprehensive health insurance.
- Flexible and remote work options.
- Professional development opportunities.
- Access to the latest tools and technologies in data engineering and business intelligence.
- Participation in a dynamic and growing field with continuous learning opportunities.
- Collaborative and supportive team environment.
- Recognition and reward for outstanding performance.
How to Stand Out
- Ensure your portfolio showcases your ability to design and develop scalable data solutions, including examples of your work with Excel, SQL, and Power BI.
- Practice explaining complex data concepts to non-technical stakeholders to demonstrate your communication skills.
- Familiarize yourself with the latest advancements in data engineering and be prepared to discuss how you stay updated with industry trends.
- Highlight any experience with cloud computing platforms like AWS or Snowflake, as well as knowledge of data governance and compliance.
- Prepare to discuss your approach to data quality testing and validation, as well as your experience with automated data tests.
- Be ready to talk about your experience with agile development methodologies and how you adapt to new technologies and initiatives.
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