Senior Software Engineer (Data Strategy) | New York, NY

Detailed Information

  • Location: New York, NY

  • Company: Real Careers

Data Strategy has a start-up style mandate (within a $2 billion company) to enhance the acquisition, storage, analysis, fidelity, and monetization of client, internal, and third-party data across the organization. This innovation spans our petabyte-scale insured assets, including property, business, marine, and aviation entities, and their associated risks, such as hurricanes, wildfires, cyber-attacks, and wars, in a financial and economic context.

As a member of the Data Strategy group, the Senior Software Engineer will work with fellow data and web engineers, data scientists, product managers, business analysts, and stakeholders from other internal groups to design and improve data-centric

projects with the dual mandate of (1) increasing the efficiency of the data collection and analysis process across the company and (2) driving the monetization of data via newly designed and existing products for their reinsurance clients.

The Senior Software Engineer will be the head facilitator on multiple innovative initiatives and will have ownership over the design, development, and delivery of projects requiring direct reporting to senior-level management in both business and technical groups. RESPONSIBILITIES: Work with a product manager as technical lead of a team of ~5 engineers, data scientists, and analysts to design, scope, and oversee work in an Agile environment. Manage

junior data and web engineers, focusing on productivity, quality, and professional development.

Partner with the head of Data Strategy and other senior engineers to create and evangelize best-in-class engineering competency and tooling within the organization. Enforce strong development standards across the team through code reviews, automated testing, and monitoring. Establish strong relationships with internal clients as an engineering representative for data strategy. Contribute to the overall Data Strategy vision and execution via quarterly planning and executive committee reporting. Partner regularly improving engineering recruiting process for the required skillsets and resourcing demands.

Learn the complex business of reinsurance to coach data technologists and execute the team's initiatives more effectively. Develop, implement, and deploy custom data pipelines powering machine learning algorithms, insights generation, client benchmarking tools, business intelligence dashboards, reporting, and new data products. Innovate new ways to leverage large and small datasets to drive revenue via the development of new products with the Data Strategy team, as well as the enhancement of existing products. Architect engineering solutions using the latest cloud technologies in a process that spans hypothesis-validating prototypes to large-scale production data products, ensuring internal security and regulatory compliance.

Design solutions that account for unstructured data and document management system(s), including ingesting, tracking, parsing, analyzing, and summarizing documents at scale. Perform exploratory and goal-oriented data analyses to understand and validate the requirements of data products and help create product roadmaps. Develop, implement, and deploy front-ends and APIs, which may involve business intelligence dashboards, data pipelines, machine learning algorithms, and file ingestion mechanisms.

QUALIFICATIONS: 5-8+ years of relevant experience in data-focused software engineering Masters Degree or Ph. D. in data science, computer science, or related quantitative field such as applied mathematics, statistics, engineering or operations research, or equivalent experience. Experience working with Python-based server-side web frameworks like Fast API or Django Strong knowledge of SQL and familiarity with the high-level properties of modern data stores. Strong understanding of the contemporary SDLC, including dev/QC/prod environments, unit/integration/UA testing, CI/CD, etc.

Experience building and maintaining CI/CD pipelines with tools such as Azure Dev Ops, Git Lab, Travis, Jenkins, etc. 2+ years of data analysis, AI, or data science work. Experience with data cleaning, enrichment, and reporting to business users. Extensive experience with (py)Spark, Python, JSON, and SQL. Experience integrating data from semi-structured and unstructured sources. Knowledge of various industry-leading SQL and No SQL database systems. Experience with or strong interest in learning about LLMs in a productized context.

ADDITIONAL QUALIFICATIONS: Strong understanding of entity resolution, streaming technologies, and ELT/ETL frameworks. Experience with web scraping and crowdsourcing technologies. Experience with Databricks and optimizing Spark clusters. Experience architecting web ecosystems from the ground up, including monolith vs. microservice decisions, caching technologies, security integrations, etc. Experience working with data visualization dashboarding tools (Power BI, Tableau). Insurance domain knowledge or strong interest in developing it. Experience with the MS Azure cloud environment. Required Knowledge, Skills, and Abilities: (Hiring Companies ATS Questions) : 1.

Do you have a Masters Degree or Ph. D. in data science, computer science, or related quantitative field such as applied mathematics, statistics, engineering or operations research, or equivalent experience.2. Do you have 5-8+ years of relevant experience in data-focused software engineering.3. Do you have 2+ years of data analysis, AI, or data science work.4. Do you have Python-based server-side web frameworks like Fast API or Django experience.5. Do you have Extensive experience with (py)Spark, Python, JSON, and SQL6. Data cleaning, enrichment, and reporting to business users - Nice to have:7.

Do you have SQL and No SQL database systems experience.8. Do you have SQL and familiarity with the high-level properties of modern data stores. Experience9. Do you have Data visualization dashboarding tools (Power BI, Tableau). experience10. Do you have Databricks and optimizing Spark clusters experience11. Do you have MS Azure cloud environment experience12. Do you have strong interest in learning about LLMs (Large Language Models) in a productized context, entity resolution, streaming technologies, ELT/ETL frameworks, web scraping, crowdsourcing technologies, Databricks, and optimizing Spark clusters.13.

Do you have Architecting web ecosystems from the ground up, including monolith vs. microservice decisions, caching technologies, security integrations, etc. - Nice to have:14. Must be a US Citizen or Green Card holder.

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