Data Engineering Consultant

Germany | Hybrid | €60,000-€85,000 (DOE) + Benefits

About the Opportunity
Omnis Partners is proud to partner with a leading global technology consultancy that combines world-class data engineering with human-centered innovation. Our client has a strong presence across industries and helps major brands transform raw data into strategic business insights through intelligent digital platforms and scalable data solutions.

We are looking for an experienced Data Engineering Consultant to join a high-performing data team, someone passionate about building data-driven ecosystems that empower business innovation and insight.

The Role
As a Data Engineering Consultant, you will design, implement, and optimize scalable data architectures and data pipelines. You will act as a bridge between raw data and actionable insights, collaborating with data analysts, architects, and data scientists to deliver high-quality, robust data solutions.

Key Responsibilities:

• Build & Scale Data Pipelines: Design and implement real-time and batch data pipelines using Apache Spark, Databricks, Snowflake, and Airflow.
• Integrate & Transform Data: Collaborate with analysts to define source-to-target mappings and maintain high data quality through ETL/ELT workflows and validation processes.
• Automate & Optimize: Automate data processes including reconciliation, error handling, and metadata management, while improving performance and cost-efficiency.
• Collaborate & Lead: Work cross-functionally with technical and business teams, mentor junior engineers, and promote best practices across CI/CD, version control, and governance.
• Governance & Compliance: Implement data security frameworks (RBAC, encryption) and regulatory compliance (GDPR), maintaining data lineage documentation.

Skills & Experience
We are looking for a Data Engineering Consultant with a balance of technical expertise, architectural vision, and collaboration skills.

• Strong programming skills in Python, SQL, and preferably Scala or Java.
• Hands-on experience with Big Data frameworks such as Apache Spark, Hadoop, Databricks, and Snowflake.
• Experience with cloud platforms: AWS (Glue, Redshift), Azure (Synapse, Data Factory), or GCP (BigQuery, Dataflow).
• Expertise in data modelling: dimensional, relational, and NoSQL databases.
• Familiarity with DevOps tools: Docker, Kubernetes, Terraform, and CI/CD pipelines.
• Strong understanding of data governance, security, and performance optimization in large-scale environments.

What’s on Offer

• Work on cutting-edge data projects across multiple industries.
• Support for continuous learning, certifications, and global career growth.
• An inclusive, collaborative culture that values diversity, innovation, and knowledge sharing.