Databricks Architect

4 weeks ago

Philadelphia, United States Hire IT People, Inc Full time

Job Title: Databricks Architect

Location: Philadelphia, PA (Onsite)

Start: Immediate

Duration: Long term

Primary Responsibilities:

Utilize consulting and technical skills to be able to work in a client-facing project environment independently.

Be responsible for your own execution and often others' on client projects, communicating directly with internal and external stakeholders on status updates and potential roadblocks.

Collaborate with other team members to successfully deliver on projects.

Work effectively and directly communicate with both internal and client and/or partner teams.

Develop full ownership of your execution on client engagements, play a role in the project planning and solution stages of engagements as well.

Lead the end-to-end implementation of multiple ETL/ELT pipelines, demonstrating efficient data transformation.

Mentor junior data engineers, and their growth is evident in their project contributions

Successfully lead small data warehousing projects with measurable performance enhancements under the management of an engagement lead- may also play the role of an engagement lead.

Contribute to real-time data processing solutions and managed streaming data.

Implement security and compliance measures for data pipelines.

Design and implement version control and branching strategies and integrate them into CI/CD for promoting and testing in higher environments.

Our Ideal Candidate's Skills and Experiences:

B.S. in Computer Science or equivalent

4-6 years' experience in data engineering and big data. 2 years' of professional services experience interacting directly with clients.

Extensive knowledge of data warehousing concepts and hands-on experience deploying pipelines using Databricks **a must

Databricks Solution Architect certification a plus.

Data modeling and database design skills and knowledge of version control

Excellent verbal and written communication skills

Experience architecting scalable and fault-tolerant data solutions across Azure, AWS, and Databricks

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