Senior Data Engineer; Databricks

* Candidates must possess work authorization which does not require sponsorship by the employer for a visa.

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 7 times most recently in 2024. Infinitive has also been named a Washington Post “Top Workplace”, Washington Business Journal “Best Places to Work”, and Virginia Business “Best Places to Work.”

Job Summary:
We are seeking a highly skilled Data Architect with extensive experience in Databricks on AWS or Azure to join our dynamic team. The ideal candidate will be responsible for designing, building, and maintaining scalable data architectures, ensuring data integrity, and optimizing data flow and collection. This role requires a deep understanding of cloud-based data solutions and strong expertise in leveraging Databricks to drive data initiatives.

Key Responsibilities:

Design, develop, and implement data architectures and solutions on Databricks in both AWS and Azure.

Collaborate with stakeholders to understand business requirements and translate them into technical specifications.

Develop and maintain ETL processes to ensure efficient data flow and integration across systems.

Ensure data quality, integrity, and security in all data-related activities.

Optimize data storage and retrieval strategies to improve performance and cost-efficiency.

Lead the implementation of data governance policies and procedures.

Provide technical guidance and mentorship to data engineering teams.

Stay updated with the latest industry trends and best practices in data architecture, Databricks, cloud data warehouses, AWS and Azure.

Required Skills and Qualifications:

Bachelor’s or Master’s degree in Computer Science, Information Technology, or related field.

Proven experience as a Data Architect, with a strong focus on Databricks.

Proficiency in Databricks, including the ability to build and optimize Spark applications.

Extensive experience with AWS services such as S3, Redshift, EMR, Lambda, Glue, and others.

Strong knowledge of Unity Catalog and its application in managing and securing data assets.

Strong knowledge of data modeling, ETL processes, and data warehousing concepts.

Proficiency in SQL and experience with big data technologies (e.g., Hadoop, Spark).

Familiarity with data governance and data security practices.

Databricks Certified Associate.

Excellent problem-solving skills and attention to detail.

Strong communication and collaboration skills.

Preferred Qualifications:

AWS Certified Solutions Architect or similar certification.

Databricks Certified Professional.

Experience with other cloud platforms (e.g., Azure, GCP).

Knowledge of machine learning and data science concepts.

Experience with data visualization tools (e.g., Tableau, Power BI).

Prior experience in a leadership or mentorship role.

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 1 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 Postgre

SQL?*

What is your experience with Mongo

DB?*

What is your experience with Snowflake?*

What is your experience with Apache Cassandra?*

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