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# Data Engineer III

- **Company:** Spectraforce
- **Location:** Quincy, MA, United States
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Microsoft Azure, Data Architecture, Information Engineering, Data Governance, Data Infrastructure, Data Integration, Data Integrity, Extract Transform Load (ETL), Distributed Computing Environment, Github, Java Database Connectivity, JSON, Python (Programming Language), Microsoft SQL Server, Performance Tuning, Scrum Methodology, SQL Databases, Technical Data Management Systems, Extensible Markup Language (XML), Data Processing, Apache Spark, Change Data Capture, Data Lakes, Pyspark, Real Time Data, Apache Kafka, Video Streaming, Software Version Control, Data Pipelines, Databricks
- **Published:** November 11, 2026
- **Apply:** http://leoforce.us/Careers/Spectraforce/JobDetails.html?jobid=5d1076e8-4e4b-4f9b-9baa-6630620f6c28&OrgId=1&UserId=3210

## About the Role

The ideal candidate brings extensive experience building end-to-end data engineering pipelines with CDC (Change Data Capture) capabilities, and thrives in a fast-paced Azure-based environment leveraging Databricks, PySpark, and Kafka streaming., * Extensive hands-on experience with Databricks, with ability to contribute from day one.

 * Proven experience building end-to-end data engineering pipelines with CDC capabilities.
 * Strong proficiency in PySpark and SQL (required); Python experience is a plus.
 * Experience working in Microsoft Azure cloud environments.
 * Knowledge of: Delta Lake, Distributed data processing frameworks, Streaming technologies (Kafka) ,Data modeling (SCD Type 1 & Type 2)
 * Experience integrating data from multiple structured and unstructured data sources.
 * Familiarity with GitHub and CI/CD pipelines for version control and deployment.
 * Strong understanding of data architecture, performance optimization, and pipeline scalability.
Key Competencies:

 * Proactive and self-driven with strong problem-solving skills
 * Ability to work across complex, evolving data environments
 * Strong collaboration and communication with technical and business teams
 * Focus on quality, scalability, and continuous improvement

## Description

We are seeking a highly skilled Databricks Data Engineer to support the Retail Spine initiative, working with a wide range of retail datasets to design, build, and optimize scalable data solutions. This role requires deep hands-on expertise in Databricks and the ability to contribute immediately by developing new pipelines while enhancing existing data workflows., * Design, build, and optimize end-to-end ETL/ELT pipelines using Databricks and Apache Spark (PySpark).

 * Develop and maintain scalable data solutions on Microsoft Azure, leveraging Databricks, Delta Lake, and Kafka streaming.
 * Build robust pipelines with Change Data Capture (CDC) to support incremental data processing and real-time/near real-time data needs.
 * Work across both new pipeline development and enhancement of existing pipelines, quickly understanding current codebases to deliver improvements.
 * Integrate and process data from diverse sources including: Flat files, XML, JSON, SQL Server and JDBC systems, Kafka topics, APIs, MQ, Unity Catalog volumes and other enterprise platforms.
 * Implement data quality frameworks, including writing technical data quality rules and quarantining error records.
 * Apply canonical data modeling techniques, including SCD Type 1 and Type 2 implementations.
 * Ensure high levels of data reliability, performance, scalability, and monitoring across all workflows.
 * Automate workflows using Databricks Workflows and CI/CD pipelines (GitHub), focusing on reuse, efficiency, and standardization.
 * Adhere to Client architecture, governance, and security standards.
 * Collaborate with developers, architects, and product owners, and engage with stakeholders, source teams, and downstream consumers as needed.
 * Participate actively in Agile/Scrum ceremonies and deliver high-quality solutions within defined timelines.