Lead Data Engineer
Role details
Job location
Tech stack
Job description
We are seeking a Lead Data Engineer to lead and coordinate our Data Engineering team. This role is pivotal in driving the delivery of high-quality, scalable, and maintainable data solutions across our organization.
You will directly coordinate the team's day-to-day work, manage project priorities, and ensure functional alignment with business objectives to deliver impactful, data-driven projects on time. You will work closely with the Principal Data Engineer to drive the application of best practices, coding standards, and architectural patterns within the team, ensuring technical excellence and consistency. A key component of this role is acting as a servant leader, removing obstacles, facilitating team success, and contributing to the strategic direction of our data platform.
Responsabilities:
- Lead and coordinate the day-to-day activities of the Data Engineering team.
- Mentor and coach team members, providing regular, constructive feedback, conducting performance check-ins, and supporting their professional growth and career development.
- Manage and prioritize the team's project backlog, translating business requirements into clear, actionable technical tasks and delivery timelines.
- Work closely with the Principal Data Engineer to implement development standards, CI/CD processes, and data architecture guidelines within the team.
- Facilitate collaboration, code reviews, and design discussions within the team.
- Coordination, development, and deployment of data pipelines, transformation models, and data integration solutions designed by Data Architecture team.
- Collaborate with other teams (Data Science, Analytics, DevOps, and Software Engineering) to align data engineering initiatives with broader company goals.
- Advocate for continuous improvement in data engineering methodologies, testing practices, and documentation.
- Encourage a culture of knowledge sharing and technical excellence within the team.
Requirements
- Bachelor's degree in Computer Science, Information Systems, or a related field.
- Proven experience as a Data Engineer, Data Architect, or similar role, with demonstrable experience in technical team leadership, coordination, or people management.
- Strong organizational, and people-management skills with the ability to motivate, coach, and guide a technical team.
- Hands-on experience with cloud technologies (AWS, Azure) and familiarity with data warehousing concepts.
- Strong proficiency in SQL, with experience in relational databases such as SQL Server and PostgreSQL, as well as data warehouses like Redshift and Snowflake.
- Solid understanding of ETL processes, data integration, and data quality management.
Experience in the following areas will be highly valued:
- Cloud providers such as Azure and AWS, including services for data storage, processing, and orchestration.
- dbt for data modeling, transformation, testing, and documentation.
- Python for software engineering, data pipelines, and automation.
- Implementation of DevOps practices, including CI/CD pipelines and automated testing.
- Experience with containerized environments using Docker and orchestration with Kubernetes.
- Workflow orchestration with Airflow.
- Data integration tools such as Fivetran and Airbyte.
- Experience with Snowflake or Redshift, including performance optimization, security, and scalability.
- Familiarity with big data processing frameworks such as Apache Spark.
- Infrastructure as Code with Terraform and cloud deployment automation.
- Strong understanding of data architecture principles, including data lakes, data warehouses, and modern cloud-native architectures.
- Knowledge of data governance, quality, and security best practices in enterprise environments.