Data Engineer

About the role

Who We Are

Konrad is an AI-driven digital consultancy and product-innovation firm providing AI, strategy, design, and technology services to the world’s most ambitious businesses and brands.

We empower industry-leading brands to navigate change, strategize, and build extraordinary custom experiences. In a landscape defined by human and machine collaboration, we bridge the gap between complex AI and beautiful product design. From strategy to implementation, our 750+ global experts deliver intelligent solutions trusted by 500 million people.

About The Role

As a Data Engineer you’ll be tasked with designing, building, and maintaining scalable data platforms and pipelines. Your deep knowledge of data platforms such as Azure Fabric, Databricks, and Snowflake will be essential as you collaborate closely with data analysts, scientists, and other engineers to ensure reliable, secure, and efficient data solutions.

What You’ll Do

- Design, build, and manage robust data pipelines and data architectures.

- Implement solutions leveraging platforms such as Azure Fabric, Databricks, and Snowflake.

- Optimize data workflows, ensuring reliability, scalability, and performance.

- Collaborate with internal stakeholders to understand data needs and deliver tailored solutions.

- Ensure data security and compliance with industry standards and best practices.

- Perform data modelling, data extraction, transformation, and loading (ETL/ELT).

- Identify and recommend innovative solutions to enhance data quality and analytics capabilities.

Qualifications

- Bachelor’s degree or higher in Computer Science, Data Engineering, Information Technology, or a related field.

- At least 3 years of professional experience as a Data Engineer or similar role.

- Proficiency in data platforms such as Azure Fabric, Databricks, and Snowflake.

- Hands-on experience with data pipeline tools, cloud services, and storage solutions.

- Strong programming skills in SQL, Python, or related languages.

- Experience with big data technologies and concepts (Spark, Hadoop, Kafka).

- Excellent analytical, troubleshooting, and problem-solving skills.

- Strong understanding of data modeling concepts including medallion architecture, data vault, grain, fact tables, dimensions, and schema design.

- Hands-on experience building and maintaining transformation layers using dbt or similar ELT tools.

- Experience building production-grade data models with optimized performance supporting operational decision-making.

- Experience designing batch and real-time ingestion frameworks with real-time monitoring

- Ability to effectively communicate technical concepts clearly to non-technical stakeholders.

Nice to have

- Certifications related to Azure Data Engineering, Databricks, or Snowflake.