Director, Data Engineering

Job not on LinkedIn

November 18

❄️ Minnesota – Remote

Although this job is listed in Minnesota, this company may be open to hiring remote in other states.

💵 $165k - $200k / year

⏰ Full Time

🔴 Lead

🚰 Data Engineer

🦅 H1B Visa Sponsor

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Livefront

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B2B • SaaS • Artificial Intelligence

Livefront is a company that helps other companies grow by creating digital products that people love. Since 2001, they have shaped the way companies win in the digital space by designing, building, and scaling core digital products and experiences. Their services include strategy consulting, design, product development, and integration of data and AI to create personalized experiences. Livefront is a trusted partner of large brands, helping them strategically implement AI to enhance the development and performance of digital products. They have worked on projects transforming educational support, smart home automation, and digital engagement for consumer brands.

11 - 50 employees

🤝 B2B

☁️ SaaS

🤖 Artificial Intelligence

📋 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.

🎯 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.