Director, Data Engineering

At Livefront, we help companies design and build world-class digital products that command attention and inspire joy. We’ve helped household names like Target, Samsung, General Mills, and Optum create experiences that have reached millions of people, and startups like HomeSpotter and Credly build entirely new businesses that challenge their industries’ status quo.

We’re looking for an outstanding Director, Data Engineering to join our team. 

Who you are

You're an expert in your field and care deeply about the craft of using data to understand consumer behavior and drive business outcomes. You are consultative, a persuasive communicator, and thrive when helping clients see the vision for how data can help them better understand their customers and grow their businesses. You lead by example, have exceptionally high standards, and have a long record of inspiring teams to do their best work. You manage competing priorities gracefully and can rally a team to execute with great results. You understand the motivations, strengths, and weaknesses of your team and cultivate an environment of learning, growth, and career development for everyone. You're a teacher and mentor, and you go out of your way to support and serve your team.

You lead major data-related decisions and initiatives, inspire collaboration and support, and drive initiatives to completion with the team. You stay informed about industry trends, participate in community and industry events, and share knowledge through regular publications and presentations. You are empathetic, curious, and always learning and improving. You are not limited by data engineering dogma, and your engineering principles are mature, fluid, and influenced by your experience, your peers, and advances in the field.

What you will be doing

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.

Excellence in Delivery & Communication

- 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.

- Stay current with AI trends, technologies, models, frameworks, eval methods, and responsible AI practices. You will proactively learn new advancements and bring these learnings to our practice in a pragmatic, applied way. You may lead or contribute to strategic spikes exploring new models, APIs, or frameworks.

- Monitor the landscape of relevant AI platforms and identify potential partnership opportunities for Livefront. You may support these partner development activities in a subject matter expert capacity.

- Support proposal writing, pre-sales discovery, and client presentations as a data and AI subject matter expert.

One-of-a-Kind Team

- Provide technical leadership, guidance, and mentorship for data engineers on the team.

- Conduct employee performance reviews and support and cultivate professional growth for the engineers directly reporting to you.

- Foster a culture of learning, ownership, accountability, and transparency for the data engineering team.

- Actively participate in the recruiting process by interviewing candidates in one-on-one or group settings and evaluating candidates’ technical abilities via interviews or code review.

Thought Leadership and Community

- Contribute to the broader data engineering community through writing, public speaking, and open source.

- Commit to at least two articles or speeches at public events each year.

- Mentor other engineers regarding community contributions.

- Participate with high visibility in community events.

• You want to work with passionate and talented people who are always looking for ways to make things better. 
• You desire a work environment where respect, mutual trust, and egoless collaboration are paramount. 
• You want colleagues who take their work seriously but not themselves, and who know how to let loose and have a good time. 
• You like being part of a team that has a reputation for excellence and gives back to the community by educating, mentoring, and sponsoring. 
• You want to work on products and accounts that have outsized impact and reach. 
• You believe in sweating the details, giving a damn about quality, and taking pride in going the extra mile.

• 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.

• Have strong illustration skills for technical diagramming and data architecture documentation.
• Have worked with real-time streaming technologies (Kafka, Kinesis, or similar).
• Have experience with cloud data platforms beyond Databricks, such as Snowflake.
• Have familiarity with machine learning pipelines and MLOps practices.
• Have experience in healthcare or fintech domains.
• Have experience with Java, Go, or Scala.
• Have contributed to open-source data projects.
• Have publicly released your own personal, self-started data products or tools.

What to expect

When applying, please include a short note about yourself, a summary of your work experience, and a link to any public profiles you actively maintain (e.g., GitHub, LinkedIn, etc).

Our hiring process moves quickly and consists of several stages for candidates who capture our attention with their initial submission, sometimes including but not limited to a short preliminary phone interview, a series of video interviews, and a short take-home exercise, which you'll have up to a week to complete.

Compensation is $165,000 - $200,000 a year. This role includes an incentive plan.

Additional information

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.