Data Engineer (Databricks Experience)

Overview

Candidates must be local to the Washington D.C. metro area.

About Infinitive: Infinitive is a data and AI consultancy that enables its clients to modernize, monetize and operationalize their data to create lasting and substantial value. We possess deep industry and technology expertise to drive and sustain adoption of new capabilities. We match our people and personalities to our clients' culture while bringing the right mix of talent and skills to enable high return on investment.

Infinitive has been named “Best Small Firms to Work For” by Consulting Magazine 8 times, most recently in 2025. Infinitive has also been named a Washington Post “Top Workplace,” Washington Business Journal “Best Places to Work,” and Virginia Business “Best Places to Work.”

About the Role

We are seeking a highly skilled Senior Data Engineer to join our dynamic team. The ideal candidate will have a strong background in data engineering, with expertise in Databricks, DevOps tools (Jenkins/Terraform), and data modeling concepts (3NF, Dimensional, Data Vault). As a Senior Data Engineer, you will play a critical role in designing, implementing, and maintaining our client\'s data infrastructure while ensuring scalability, reliability, and efficiency.

Responsibilities

• Data Engineering: Design, build, and maintain scalable data pipelines and ETL processes using Databricks and other relevant technologies.
• DevOps Integration: Implement CI/CD pipelines using Jenkins and Terraform to automate deployment, monitoring, and scaling of data infrastructure.
• Data Modeling: Develop and implement data models based on business requirements, including 3NF, Dimensional, and Data Vault models. Ensure data models adhere to best practices for efficiency, scalability, and maintainability.
• Performance Optimization: Identify and address performance bottlenecks in data pipelines and queries. Optimize data processing and storage to improve overall system performance.
• Data Quality Assurance: Implement data quality checks and monitoring processes to ensure data accuracy, completeness, and consistency.
• Collaboration: Work closely with cross-functional teams including data scientists, analysts, and software engineers to understand data requirements and deliver high-quality solutions.
• Documentation and Best Practices: Document data pipelines, infrastructure configurations, and data models. Define and enforce best practices for data engineering and DevOps processes.
• Training and Mentorship: Provide guidance and mentorship to junior team members. Conduct training sessions to promote knowledge sharing and skill development within the team.

Qualifications

• Bachelor’s degree in Computer Science, Engineering, or related field. Master’s degree preferred.
• Proven experience as a Data Engineer, preferably in a cloud-based environment.
• Strong proficiency in Databricks for data processing and analytics.
• Hands-on experience with DevOps tools such as Jenkins and Terraform for infrastructure automation.
• In-depth knowledge of data modeling concepts including 3NF, Dimensional, and Data Vault.
• Proficiency in SQL and programming languages such as Python or Scala.
• Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform.
• Excellent problem-solving skills and attention to detail.
• Strong communication and collaboration skills.

Applicants for employment in the U.S. must possess work authorization which does not require sponsorship by the employer for a visa.

Infinitive is an Equal Opportunity Employer.

Are you currently legally authorized to work in the US for any employer?

Do you now or will you ever require sponsorship from Infinitive to continue to be authorized to work in the US?

Are you local to the Washington DC/Metro area?

Do you have at least 3 year of experience in data engineering?

What is your experience with SQL?

What is your experience with ETL?

What is your experience with Python?

What is your experience with PySpark?

What is your experience with Apache Spark?

What is your experience with Amazon Redshift?

What is your experience with Databricks?

What is your experience with PostgreSQL?

What is your experience with MongoDB?

What is your experience with Snowflake?

What is your experience with Apache Cassandra?

What is your experience with the ELK stack (Elastic, Logstash, Kibana)?