Livefront

We help companies grow by creating digital products people love.

Director, Data Engineering

Data EngineerData EngineerFull TimeRemoteTeam 11-50H1B SponsorCompany SiteLinkedIn

Location

Minnesota

Posted

114 days ago

Salary

$165K - $200K / year

Bachelor Degree7 yrs expEnglishAWSAzureCloudETLGoogle Cloud PlatformPythonSparkSQL

Job Description

• As a Director of Data Engineering at Livefront, you will lead the data practice covering data engineering, data science, machine learning, and data analytics. • This is a billable role where you will employ a "lead by example" style of leadership. • In addition to client work, you will mentor, support, and manage the engineers reporting directly to you. • You will work with Livefront Client Partners and the rest of the Livefront team to create and refine the overall technical vision for our data engagements. • You will participate in technical discovery, advocate for Livefront's engineering philosophy and approach, choose the right technologies to solve the problem, and see projects through to completion. • You will collaborate with Livefront leadership to push everything we do forward across our three pillars, noted below. • Help shape the direction of an emerging data practice at Livefront. • Work with the data team to continually refine our architectures, platforms, and engineering standards and facilitate the adoption of those ideas across the team and our client projects. • Architect and oversee the design of scalable, secure, and performant data systems across a variety of cloud environments (e.g., AWS, Azure, GCP) and data platforms (e.g., Databricks, Snowflake). • Define our standards for data engineering, code reviews, testing, security, performance monitoring, and data governance, and ensure conformance with those standards across all our projects. • Plan, estimate, and execute data engineering initiatives for the organization and our client projects. • Ensure the security, privacy, and compliance of all data systems, pipelines, and products. • Roll up your sleeves and work directly in the codebase frequently. • Create architecture diagrams, data flow diagrams, and other technical illustrations to enable effective communication regarding technical requirements.

Job Requirements

  • Experience leading data engineering teams.
  • Experience leading or working very closely with data scientists, machine learning engineers, and data analytics professionals.
  • Experience teaching, mentoring, and motivating data engineers.
  • Deep expertise with Databricks as a developer, architect, and practice leader, including proficiency with Spark and large-scale data processing.
  • Experience with strategic planning, leading and facilitating technical problem solving, designing data solutions in a team environment, and motivating and managing teams to successful execution.
  • Experience setting and maintaining standards and expectations for data engineering best practices, code reviews, testing, and data observability.
  • At least 7–10 years of data engineering experience, ideally in a consulting environment or as part of an in-house, cross-functional product team.
  • Proven experience designing and implementing data warehousing solutions at scale.
  • Expertise in building production ETL/ELT pipelines with a focus on reliability and performance.
  • Deep understanding of cloud data platforms (AWS, Azure, and GCP) with the ability to architect solutions on any of them.
  • Strong proficiency in SQL and Python with the ability to write clean, performant, and maintainable code.
  • Strong understanding of data modeling, schema design, and query optimization.
  • Knowledge of data governance, security best practices, and compliance requirements.
  • Excellent communication skills and a strong ability to present and defend technical and architectural choices persuasively.
  • Renowned problem-solving skills.
  • Above-average discipline and personal organization skills.
  • A demonstrated hunger for personal and professional growth.
  • A self-evident love and care for the craft of data engineering.

Benefits

  • We go out of our way to evaluate all employees and job applicants equally based on merit, competence, and qualifications.
  • We encourage candidates from all backgrounds to apply and consider all qualified applicants.
  • Don't worry, every application will be reviewed by a human.

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