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# Software Engineer

- **Company:** Kforce Inc.
- **Location:** Boston, MA, United States (Remote available)
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Amazon Web Services, Business Analytics Applications, Automation of Tests, Microsoft Azure, Cloud Engineering, Code Review, Databases, Continuous Integration, Data Architecture, Information Engineering, Data Governance, Data Integration, Software Debugging, DevOps, Distributed Computing Environment, Identity and Access Management, Information Lifecycle Management, Python (Programming Language), Performance Tuning, Cloud Services, Standard Sql, SQL Databases, Enterprise Data Management, Google Cloud, Cloud Platform System, Software Troubleshooting, Change Data Capture, Data Lakes, Pyspark, Infrastructure Automation Frameworks, Deployment Automation, Data Management, Video Streaming, Software Version Control, Data Pipelines, Databricks
- **Published:** September 30, 2026
- **Apply:** https://www.dice.com/job-detail/9f48ce40-8e1c-43e9-9a73-1d4dc4b8afc2

## About the Role

* 7+ years of experience in data engineering, data architecture, or platform engineering, including significant experience with Databricks
 * Current hands-on development experience with Python/PySpark and advanced SQL in production environments
 * Experience with Databricks technologies, including Delta Lake, Unity Catalog, workflows, SQL capabilities, and related platform services
 * Experience designing enterprise-scale data architectures and supporting data across multiple business domains
 * Experience with Infrastructure as Code, automated deployments, CI/CD pipelines, and modern DevOps practices
 * Proven experience with platform performance tuning, monitoring, capacity planning, and cost optimization
 * Experience integrating data platforms with APIs, databases, streaming technologies, and business intelligence solutions
 * Deep knowledge of modern lakehouse architecture, distributed data processing, data governance, and enterprise data platforms
 * Strong understanding of cloud architecture across Azure, AWS, or Google Cloud Platform, including storage, networking, security, and identity management
 * Strong knowledge of data modeling, data quality, lineage, change data capture, and integration patterns
 * Strong troubleshooting and root-cause analysis skills in complex production environments
 * Excellent communication skills with the ability to explain technical concepts to both technical and business stakeholders
 * Demonstrated technical leadership, mentoring, and ability to influence engineering standards across teams
 * Proven ability to develop, debug, review, and optimize complex data pipelines and transformations

## Description

Kforce has a client that is seeking Senior Software Engineer in Boston, MA., * Design and lead scalable enterprise data platform architecture using modern cloud and lakehouse technologies

 * Establish architectural standards for data engineering, data modeling, governance, integration, and platform development
 * Provide hands-on technical leadership through code reviews, troubleshooting, performance tuning, and solution design
 * Develop and optimize complex data pipelines and transformations using Python/PySpark and SQL
 * Define platform security, access controls, data governance, lineage, and compliance standards
 * Design CI/CD, source control, automated testing, and Infrastructure as Code practices for data platforms
 * Establish scalable approaches for compute, storage, workload management, resiliency, and cost optimization
 * Define enterprise standards for data quality, schema design, change data capture, and data lifecycle management
 * Design integrations between source systems, cloud services, analytics platforms, and downstream applications
 * Monitor and optimize platform performance, reliability, capacity, and operational efficiency
 * Partner with engineering, architecture, analytics, and business teams to translate requirements into technical solutions
 * Mentor data engineers and promote consistent engineering practices across teams
 * Evaluate emerging data and AI capabilities and recommend technologies that provide measurable business value
 * Maintain architecture documentation, technical standards, and knowledge-sharing practices


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