DriveTime · 5 hours ago

Data Engineering Manager

Remote, US

Full-time

Remote

Mid, Senior Level

5+ years exp

Maximize your interview chances

AutomotiveFinancial Services

Actively Hiring

No H1B

Insider Connection @DriveTime

Discover valuable connections within the company who might provide insights and potential referrals.
Get 3x more responses when you reach out via email instead of LinkedIn.

Responsibilities

Lead a team of data engineers to build strategic data solutions that help redefine how we do business -- and keep us ahead of our competitors.

Collaborate with other engineers to work on key features across DriveTime.

Mentor incredibly smart, friendly, and passionate team.

Drive several exciting initiatives, help solve problems, no matter how big or small, work on business-critical projects built around cutting-edge technologies, and convey strategy and accuracy to our top-level decision-makers.

Qualification

Find out how your skills align with this job's requirements. If anything seems off, you can easily click on the tags to select or unselect skills to reflect your actual expertise.

SnowflakeAdvanced SQLData EngineeringRedshiftBigQueryMicrosoft SQLMongoDBCouchDBCassandraETL/ELTAzureAWSDatabase design

Required

5+ years of professional development experience and have led teams informally or formally on large projects and has had direct reports at some point in the past.

Advanced SQL knowledge

Ability to establish cross-functional, collaborative relationships with business and technology partners

End to end understanding of database design concepts, from transactional system design to modern data warehouse architectures

Strong problem-solving skills

Communicates clearly and concisely, both orally and in writing

Passionate about continuous learning

Bachelor’s Degree in Information Technology or related field

Snowflake, Redshift, BigQuery or another big data platform

Relational and non-relation database experience (Microsoft SQL, MongoDB, CouchDB, Cassandra, etc…)

Familiarity with modern data pipelines and ETL/ELT patterns and tools

Azure, AWS