Top Senior Level Data Engineer Jobs in Washington DC

Design and develop data models in Snowflake with DBT, write advanced SQL queries for ELT and data warehousing, collaborate with business partners, promote self-service reporting, and ensure data governance and privacy standards.

Join Iodine Software as a Senior Site Reliability Engineer specializing in managing and growing data platforms. Collaborate with teams on infrastructure projects and provide database performance consultations. Engineer solutions for expanding infrastructure.

Lead and contribute to developing and implementing machine learning models and algorithms for a tech company in the TV advertising industry, focusing on scalability, performance, and innovation. Responsibilities include designing and optimizing models, preprocessing data, deploying models, mentoring junior engineers, and collaborating with cross-functional teams. Requires 10+ years of experience in backend systems with a specialization in machine learning, a degree in Computer Science or related field, familiarity with core ML technologies, and expertise in machine learning algorithms.

Seeking a Senior Manager, Data Engineering at Capital One Software. Responsibilities include leading a team of developers, collaborating on technical solutions, utilizing programming languages and cloud services, and providing technical and people leadership. Requires 8 years of application development experience and expertise in big data technologies and cloud computing.

Senior Data Consultant specializing in data conversions, responsible for designing, configuring, and testing the Origami platform to meet client needs. Responsibilities include configuring the platform, building integrations, designing data conversion mappings, and collaborating with technical resources. Required qualifications include 6+ years of software design and implementation experience, Bachelor's Degree in a related field, and proficiency in JavaScript, XML, SQL, and Visual Basic.

Responsible for defining and driving data governance within the Finance organization. Partnering with leaders and process owners to implement data policies and standards, drive vision and strategy for elevating data as a critical enterprise asset, establish relationships with finance and technical teams, develop financial data quality metrics, manage data governance policies, maintain knowledge of financial applications, develop data capture strategies and automation, and maintain a data dictionary of key Finance data attributes.