Data Team Lead

Driivz, a Vontier company, powers the e-mobility revolution with a market-leading, end-to-end EV charging and energy management platform for global charge point operators and electric mobility service providers.

We offer a scalable, integrated solution that enables our clients to efficiently manage their networks and provide EV drivers with an exceptional charging experience.

Operating in over 30 countries across the US, Europe, and Asia, we facilitate hundreds of millions of charging events for millions of EV drivers and manage more than 100,000 public chargers (with hundreds of thousands available through roaming).

Our customers include global industry leaders such as EVgo, Volvo Group, Shell, Circle K, Mer, Recharge, Kople, ESB, CEZ, MOL Group, and eMobility Power.

Join our team and collaborate with some of the brightest and most innovative minds driving the e-mobility industry forward and building a greener future.

For more information, please visit

About the Role:

We are looking for a
hands-on Data Team Lead
to guide and scale our data, analytics, and AI-driven insights capabilities.

In this role, you will lead a team of data engineers and Tableau developers, driving the design, development, and maintenance of modern, scalable data solutions.

You'll play a key role in shaping our data flows, influencing architecture decisions, and enabling data- and AI-driven decision-making across the organization.

You will also be responsible for fostering the integration of AI/ML models into our data ecosystem, unlocking predictive and prescriptive analytics that power smarter business decisions and enhance our platform's value for customers worldwide.

Key Responsibilities:

• Lead, mentor, and support a team of data engineers and BI developers (Tableau).
• Own the end-to-end delivery of data pipelines, analytics workflows, and AI-driven insights.
• Design, build, and optimize
  ETL
  processes using tools like
  DBT
  ,
  Snowpipe
  , and
  Snowflake
  .
• Collaborate with cross-functional teams to understand data needs and translate them into scalable BI and AI solutions.
• Drive the integration of AI/ML models into reporting, forecasting, anomaly detection, and optimization use cases.
• Ensure high standards in data quality, consistency, and reliability across the data platform.
• Define and promote best practices in data modeling, transformation, dashboard development, and AI/ML deployment.
• Stay current with emerging trends in AI, analytics, and data engineering to continuously evolve our capabilities.
• Act as the technical escalation point for complex data issues, BI challenges, and AI integration.

Requirements:

• 5+ years
  of experience in
  data engineering
  with strong
  hands-on experience
  in
  ETL
  /
  ELT
  pipelines,
  DBT
  ,
  Snowpipe
  ,
  Snowflake
  , and
  Tableau
  or similar visualization tools.
• 2+ years
  of experience
  leading a team of data engineers and BI developers
  .
• Proven track record of delivering high-quality data solutions in complex environments.
• Strong understanding of data modeling, data warehousing, and analytics best practices.
• Experience in applying AI/ML techniques (e.g., forecasting, clustering, anomaly detection, recommendation systems) to real-world data problems.
• Familiarity with AI/ML platforms, frameworks, and cloud-native AI services (e.g., SageMaker, Vertex AI, Databricks, or similar).
• Experience with multi-tenant and SaaS data platforms.
• Familiarity with CI/CD for data pipelines and version control for data transformations.
• Exposure and understanding of cloud environments (AWS, GCP).
• Experience with workflow orchestration tools.
• Ability to operate both strategically and tactically, with a passion for building and mentoring teams.
• Excellent communication skills and the ability to work with stakeholders at all levels.

Preferred Qualifications:

• Master's degree in Computer Science, Data Engineering, or a related field.
• Experience leading multi-disciplinary teams (data engineering, BI, and data science).
• Hands-on experience with real-time data streaming technologies (e.g., Kafka, Kinesis, Pulsar).
• Knowledge of MLOps practices and tools for managing the lifecycle of AI/ML models.
• Familiarity with data governance, data cataloguing, and compliance frameworks (GDPR, CCPA, etc.).
• Strong knowledge of performance optimization for large-scale, multi-tenant SaaS platforms.
• Experience with advanced analytics or AI-enabled BI platforms (e.g., ThoughtSpot, Looker ML, Power BI with AI integration).
• Background in domains such as energy, fintech, mobility, or other industries with large-scale, high-velocity data.

Core Competencies:

• Technical Excellence:
  Demonstrates expertise in designing and delivering scalable, modern data solutions. Continuously seeks to deepen technical knowledge and apply best practices in data engineering and analytics.
• Business Acumen:
  Understands business goals and challenges, ensuring data initiatives align with organisational strategy and deliver measurable impact.
• Ownership & Accountability:
  Takes responsibility for project delivery, team performance, and quality standards. Proactively manages risks and communicates dependencies.
• Collaboration:
  Fosters a culture of teamwork and knowledge sharing, building strong partnerships with cross-functional teams.
• Adaptability:
  Embraces change, thrives in fast-paced environments, and guides the team through shifting priorities with resilience and focus.
• Leadership & Mentorship:
  Provides guidance, support, and coaching to team members, empowering them to grow and deliver at their best.