> Markdown version of [/jobs/ext/4624296-boston-preferred-data-engineer](https://www.wearedevelopers.com/jobs/ext/4624296-boston-preferred-data-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Boston Preferred - Data Engineer - **Company:** Kforce Inc. - **Location:** Armonk, NY, United States - **Experience:** Expert - **Contract:** Contract - **Skills:** Application Programming Interfaces (APIs), Agile Methodology, Artificial Intelligence, Data Analysis, Microsoft Azure, Big Data, Cloud Computing, Databases, Data Discovery, Information Engineering, Extract Transform Load (ETL), Data Systems, Data Warehousing, Database Schema, Python (Programming Language), NoSQL, Object-Oriented Software Development, Standard Sql, Azure Data Lake, Software Engineering, SQL Databases, Systems Integration, Snowflake, Pyspark, Information Technology, Apache Flink, Data Analytics, Apache Kafka, Data Management, Data Pipelines, Serverless Computing, Databricks - **Published:** November 7, 2026 - **Apply:** https://www.dice.com/job-detail/6fa52506-7ad2-4fbf-ba5c-ae356e94aa7e ## About the Role * 4-year college degree or equivalent combination of education and experience; Prefer an academic background in Computer Science, Mathematics, Statistics, or related technical field * 5 years of relevant work experience in analytics, data engineering, business intelligence or related field * Skilled in object-oriented programming (Python in particular) * Strong experience in Python, PySpark and SQL * Strong experience in Databricks * Experience developing integrations across multiple systems and APIs * Experience with or knowledge of Agile software development methodologies * Experience with cloud-based databases, specifically Azure technologies (e.g., Azure data lake, ADF, Azure DevOps and Azure Functions) * Experience using SQL queries as well as writing and perfecting SQL queries in a business environment with large-scale, complex datasets * Experience with data warehouse technologies. Experience creating ETL and/or ELT jobs * Excellent problem solving and troubleshooting skills * Process oriented with great documentation skills * This position requires an innovative software engineer who is passionate about data and data quality * The ideal candidate will have strong data warehousing and API integration experience and the ability to develop scalable data pipelines that make data management and analytics/reporting faster, more insightful, and more efficient Nice to have: * Experience designing data schemas and operating SQL/NoSQL database systems is a plus * Experience in Kafka, Flink, Fivetran and Matillion is nice to have * Experience in Data Science and Machine Learning is nice to have * Experience in software engineering * Experience in Snowflake ## Description Kforce has a client that is seeking a Data Solutions Engineer in San Antonio, TX., The P&C Data & Risk organization is looking for a hands-on Data Solutions Engineer/Senior Data Analyst to support a short-term, high-priority data enablement initiative. This individual will support the Lead Advisor within P&C Risk responsible for data analytics, AI, and broader data initiatives across the organization. The immediate objective is to complete a proof of concept focused on improving access to P&C source data and making that data consumable for analytics and risk use cases. The team currently has access to portions of the data but does not have complete visibility into the source data across different domains and layers. This person will help explore what is available, understand how the data is structured and accessed, move or transform data where necessary, and ultimately create curated Snowflake views and datasets that can be consumed by the business. This is an enablement and acceleration role. The goal is to give the team additional technical capacity to move this work forward quickly while establishing a foundation that could support expanded analytics initiatives in the future., * Use SQL within Snowflake to explore source data, tables, schemas, relationships, and data elements * Perform hands-on exploratory data analysis and data discovery to determine what data exists and how it can be used * Understand data that may sit across different architectural layers, systems, and business domains * Create and work with Snowflake views, tables, schemas, and curated datasets * Take underlying source data and transform it into a clean, consumable view for downstream analytics * Support the movement or ingestion of source data into Snowflake when information is not already available through existing Snowflake views