Data Engineer

As a Data Engineer at Sila, you will play a critical role in designing, developing, and maintaining the data infrastructure and cloud platform that supports our clients’ business needs. The ideal candidate will be an experienced software engineer with a passion for data management and prepared to dive in as needed to support application teams. You will collaborate with data scientists, analysts, subject-matter experts, and other stakeholders to ensure efficient data pipelines, reliable systems, and actionable insights, and to provide strategic advice on data management, data optimization, and data architecture. 

You will bring your strong analytical skills, ability to interpret data, and exceptional communication and interpersonal skills to the data platform team, while building strong client relationships. Significant collaboration is required in this role, as is the ability to work independently in a fast-paced environment.  

This candidate is preferred to be located in the Seattle Metropolitan area and may be expected to be in-person at our client locations up to 5 days a week. 

Responsibilities: 

Engage with Clients: Understand clients' business challenges and objectives, providing expert advice on data strategy and transformation. 

 Collaboration: Work closely with cross-functional teams, including data scientists, analysts, and software engineers, to understand data requirements and deliver solutions. 

Continuous Improvement: Stay up to date on the latest data management trends, emerging technologies, tools, and best practices to ensure continuous improvement and innovation, delivering cutting-edge solutions to clients. 

Required 

Database Query: Experience building complex and efficient SQL queries to combine data from multiple sources and databases. 

 Development: Bring proficiency in programming languages such as R, Python, or Java to build data ingestion scripts, data transformation scripts, and APIs to access data from source systems and provide the data to application layers. 

 Data Pipeline Development: Design, develop, and maintain scalable and reliable pipelines in IBM DataStage to process and integrate data from various sources into centralized data warehouses or lakes; create data cleansing and transformation processes. 

Data Quality Assurance: Implement data validation, cleansing, and monitoring processes to ensure data integrity and accuracy; drive data quality reports. 

API Management: Proven experience in designing, building, and using robust APIs. The ideal candidate will play a key role in enabling seamless data integration across systems, ensuring scalable and secure access to data assets. A strong understanding of RESTful principles, authentication protocols, and best practices in API lifecycle management is essential to support both internal and external data consumers. 

Cloud Infrastructure: Deploy and manage cloud-based data storage and processing solutions, leveraging an AWS platform or other cloud providers such as Google or Azure. 

Documentation: Create and maintain clear documentation for data workflows, data models, systems, and processes; identify and document data sources and build interface control documents (ICDs) for APIs; develop deployment instructions for pipelines; develop user guides and training materials for developers to access APIs. 

Soft Skills: Strong problem-solving abilities, exceptional attention to detail, and the ability to communicate complex technical concepts effectively to both technical and business stakeholders. 

Preferred 

Database Management: Build, optimize, and manage database architectures, ensuring high availability, security, and performance. Understanding of relational, dimensional, and graph database theory.  

Data Modeling: Create logical and physical data models, apply schema design principles, and set modeling standards for data platforms, data lakes, or data mesh. 

Data Governance: Familiarity with data governance and compliance requirements, such as GDPR and CCPA, and the application of governance policies and procedures; identify and document governance standards. 

Automation and Optimization: Identify and implement opportunities to streamline data workflows and improve processing efficiency; experience with containerization and orchestration tools is preferred. 

Qualifications: 

Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field. 

Minimum of 5 years of experience in data engineering or related roles. 

Experience working in SAFe/Agile teams. 

Please note: We are unable to provide sponsorship for this role. US Citizens or Greencard holders only.

Salary : $100,000 - $180,000