Senior Data Engineer

JSAN Consulting Group; Stockholms kommun; On-site; SEK 1,600,000 - 2,300,000; Full time

Job summary

JSAN Consulting Group seeks an Engineering Manager to lead Data Engineers and Analytics Engineers, delivering data products in a modern cloud data stack. You will balance people leadership with hands-on technical guidance, challenging designs while coaching senior engineers across data platforms.

The role involves driving delivery, maintaining quality, and shaping the engineering culture through collaboration with Product Managers, Architects, and stakeholders.

Qualifications

• Proven experience leading engineering teams in data/analytics domains.
• Strong background in Data Engineering, Analytics Engineering, or Data Platform development.
• Experience with Snowflake, dbt, and large-scale SQL development.
• Ability to guide architectural discussions and coach senior engineers.

Responsibilities

• Lead, coach, and develop a team of Data Engineers and Analytics Engineers.
• Drive performance management, career development, and employee engagement.
• Build a strong engineering culture focused on accountability, collaboration, and continuous improvement.
• Support recruitment, onboarding, and team growth activities.
• Own delivery planning, prioritization, and execution for the engineering team.
• Ensure commitments are delivered with high quality and manage risks/technical debt.
• Work with Product Managers, Architects, and Stakeholders to align priorities.

Skills

Leadership

People leadership

Stakeholder management

Cross-functional collaboration

Strong communication

Technical credibility

Tools

Snowflake

dbt

SQL

Airflow

Python

Cloud platforms (Azure/AWS)

Job description

The Engineering Manager will lead a team of Data Engineers and Analytics Engineers responsible for building and evolving business-critical data products and capabilities.

The team works primarily within a modern data ecosystem leveraging Snowflake, dbt, SQL, and cloud-native technologies.

The role combines people leadership, delivery ownership, and technical leadership. The successful candidate should be able to build high-performing teams, drive delivery of complex data initiatives, and provide technical guidance across data engineering, analytics engineering, and data product development.

This is not a pure people management role. To be successful, the Engineering Manager should have sufficient technical credibility to challenge design decisions, support architectural discussions, and effectively coach senior engineers working with modern data platforms.

Key Responsibilities

• Lead, coach, and develop a team of Data Engineers and Analytics Engineers.
• Drive performance management, career development, and employee engagement.
• Build a strong engineering culture focused on accountability, collaboration, and continuous improvement.
• Support recruitment, onboarding, and team growth activities.

Delivery Leadership

• Own delivery planning, prioritization, and execution for the engineering team.
• Ensure commitments are delivered predictably and with high quality.
• Manage dependencies, risks, and technical debt.
• Work closely with Product Managers, Architects, and Business Stakeholders to align priorities and outcomes.

Technical Leadership

• Provide guidance on data engineering and analytics engineering best practices.
• Support technical decisions related to Snowflake, dbt, SQL, data modeling, and data architecture.
• Promote scalable, maintainable, and well-governed data products.
• Drive adoption of engineering best practices including testing, CI/CD, documentation, and observability.

Candidates should demonstrate experience in most of the following areas:

• Previous experience leading engineering teams.
• Strong background in Data Engineering, Analytics Engineering, or Data Platform development.
• Experience working with Snowflake and modern cloud-based data platforms.
• Experience with dbt and large-scale SQL development.
• Strong understanding of data modeling concepts, including dimensional modeling and business-oriented data design.
• Experience delivering business-facing data products rather than only building technical infrastructure.
• Experience working in cross-functional environments involving Product Managers, Business Stakeholders, Architects, and Engineers.
• Strong communication and stakeholder management skills.
• Experience balancing delivery commitments, team development, and technical quality.

Preferred Experience

The following experience is considered particularly valuable:

• Leadership experience within Snowflake and dbt-centric data ecosystems.
• Experience managing Analytics Engineering teams.
• Experience with Airflow or similar orchestration technologies.
• Experience with cloud platforms such as Azure or AWS.
• Familiarity with Python and modern ELT architectures.
• Experience leading distributed or global teams.
• Experience working with customer, commercial, marketing, or digital data domains.
• Experience establishing engineering standards and operating models for data teams.