This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Director, Data Engineering in the United States.

This role leads the data engineering practice, overseeing data engineering, analytics, machine learning, and data science initiatives across complex, large-scale projects. You will set technical direction, define standards, and ensure delivery excellence while actively mentoring and managing a team of engineers. Working closely with cross-functional stakeholders, you will drive architecture decisions, implement scalable data solutions, and apply your expertise to optimize client outcomes. This position blends technical leadership with hands-on execution, offering opportunities to influence strategy, advance engineering practices, and contribute to thought leadership in the data community. It is ideal for someone passionate about shaping a high-performing team and pushing the boundaries of data-driven innovation.

Accountabilities
Lead and manage the data engineering team, providing mentorship, guidance, and professional development support.
Architect and oversee the design of scalable, secure, and high-performance data systems across cloud environments (AWS, Azure, GCP) and platforms (Databricks, Snowflake).
Define and enforce engineering standards, best practices, code review processes, testing, and data governance across projects.
Plan, estimate, and execute data engineering initiatives, ensuring alignment with business and client objectives.
Ensure security, privacy, and compliance of all data systems and pipelines.
Act as a hands-on contributor, writing code, creating architecture diagrams, and reviewing technical designs.
Stay current with AI, machine learning, and data engineering trends, incorporating new technologies and frameworks into practice.
Support pre-sales activities, client presentations, and technical discovery as a subject matter expert.
Contribute to community and thought leadership through publications, speaking engagements, and open-source projects.
Requirements
7–10+ years of experience in data engineering, ideally with experience leading teams in consulting or cross-functional product environments.
Proven leadership in managing data engineers, data scientists, and analytics professionals.
Deep expertise with Databricks, Spark, and large-scale data processing; strong proficiency in SQL and Python.
Experience designing and implementing scalable data warehousing and ETL/ELT pipelines.
Solid understanding of cloud data platforms (AWS, Azure, GCP) and ability to architect solutions across multiple environments.
Strong knowledge of data modeling, schema design, query optimization, data governance, security, and compliance best practices.
Excellent communication and presentation skills, capable of influencing technical and non-technical stakeholders.
Demonstrated ability to balance hands-on execution with strategic leadership.
Bonus experience: real-time streaming technologies (Kafka, Kinesis), machine learning pipelines/MLOps, additional programming languages (Java, Go, Scala), open-source contributions, or domain expertise in healthcare/fintech.
Benefits
Competitive salary range: $165,000–$200,000, plus incentive plan.
Flexible work arrangements, including remote options.
Comprehensive health, dental, and vision coverage.
Professional growth opportunities, mentoring, and leadership development.
Inclusive and collaborative culture emphasizing learning, transparency, and accountability.
Opportunities to contribute to community and thought leadership initiatives.

Jobgether is a Talent Matching Platform that partners with companies worldwide to efficiently connect top talent with the right opportunities through AI-driven job matching.

When you apply, your profile goes through our AI-powered screening process designed to identify top talent efficiently and fairly.

🔍 Our AI evaluates your CV and LinkedIn profile thoroughly, analyzing your skills, experience, and achievements.

📊 It compares your profile to the job’s core requirements and past success factors to determine your match score.

🎯 Based on this analysis, we automatically shortlist the three candidates with the highest match to the role.

🧠 When necessary, our human team may perform an additional manual review to ensure no strong profile is missed.

The process is transparent, skills-based, and free of bias — focusing solely on your fit for the role. Once the shortlist is completed, we share it directly with the company that owns the job opening. The final decision and next steps (such as interviews or additional assessments) are then made by their internal hiring team.

Thank you for your interest!

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We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

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