Beschreibung
Freelance Opportunity: Head of Data Engineering
Location: Berlin, 2 days on-site, 3 days remote
Start Date: ASAP
Duration: 6 months (open to extension to perm)
About Us
Our client is a fast-scaling technology company based in Berlin, focused on delivering innovative, data-driven solutions that make a measurable impact. With an international and collaborative team culture, they are passionate about harnessing data to drive growth, insight, and operational excellence.
Role Overview
They are seeking a freelance Head of Data Engineering to lead and evolve their data engineering function. This is a high-impact role responsible for setting the data engineering strategy, scaling infrastructure, and managing a team of engineers. You will work closely with product, analytics, and executive leadership to ensure the company’s data foundations are robust, future-proof, and aligned with business goals.
Key Responsibilities
Define and own the data engineering roadmap and architecture.
Lead, mentor, and scale a high-performing data engineering team.
Oversee the design and implementation of scalable and secure data pipelines.
Collaborate cross-functionally to align data infrastructure with business needs.
Champion data quality, governance, and compliance best practices.
Guide technology choices and implement modern data stack tools.
Ensure platform reliability and performance through monitoring and optimisation.
Drive adoption of best practices in code quality, testing, and CI/CD.
Maintain documentation and contribute to a strong engineering culture.
Requirements
8+ years of experience in data engineering, with 2+ years in a leadership role.
Proven track record of designing and scaling data platforms in cloud environments (AWS, GCP, or Azure).
Deep expertise in Python, SQL, and data architecture best practices.
Experience with tools such as dbt, Airflow, Fivetran, Snowflake, Redshift, or BigQuery.
Strong stakeholder management and communication skills.
Familiarity with data privacy, governance, and GDPR compliance.
Passion for building scalable systems and leading high-impact teams.
Nice to Have
Experience with real-time data processing technologies (Kafka, Spark, Flink).
Background in BI or analytics tools like Looker, Power BI, or Tableau.
Exposure to ML/AI infrastructure and MLOps practices.
If this sounds like the right fit, or you'd like to explore other opportunities, please reach out with your CV or contact us at
Location: Berlin, 2 days on-site, 3 days remote
Start Date: ASAP
Duration: 6 months (open to extension to perm)
About Us
Our client is a fast-scaling technology company based in Berlin, focused on delivering innovative, data-driven solutions that make a measurable impact. With an international and collaborative team culture, they are passionate about harnessing data to drive growth, insight, and operational excellence.
Role Overview
They are seeking a freelance Head of Data Engineering to lead and evolve their data engineering function. This is a high-impact role responsible for setting the data engineering strategy, scaling infrastructure, and managing a team of engineers. You will work closely with product, analytics, and executive leadership to ensure the company’s data foundations are robust, future-proof, and aligned with business goals.
Key Responsibilities
Define and own the data engineering roadmap and architecture.
Lead, mentor, and scale a high-performing data engineering team.
Oversee the design and implementation of scalable and secure data pipelines.
Collaborate cross-functionally to align data infrastructure with business needs.
Champion data quality, governance, and compliance best practices.
Guide technology choices and implement modern data stack tools.
Ensure platform reliability and performance through monitoring and optimisation.
Drive adoption of best practices in code quality, testing, and CI/CD.
Maintain documentation and contribute to a strong engineering culture.
Requirements
8+ years of experience in data engineering, with 2+ years in a leadership role.
Proven track record of designing and scaling data platforms in cloud environments (AWS, GCP, or Azure).
Deep expertise in Python, SQL, and data architecture best practices.
Experience with tools such as dbt, Airflow, Fivetran, Snowflake, Redshift, or BigQuery.
Strong stakeholder management and communication skills.
Familiarity with data privacy, governance, and GDPR compliance.
Passion for building scalable systems and leading high-impact teams.
Nice to Have
Experience with real-time data processing technologies (Kafka, Spark, Flink).
Background in BI or analytics tools like Looker, Power BI, or Tableau.
Exposure to ML/AI infrastructure and MLOps practices.
If this sounds like the right fit, or you'd like to explore other opportunities, please reach out with your CV or contact us at