Senior Data Engineer

About TechBiz Global

TechBiz Global is a leading recruitment and software development company. Our diverse, globally distributed team provides IT recruitment, outstaffing, outsourcing, software development, and different consulting services with a primary focus on making our partners achieve their business goals successfully.

With headquarters in Germany we have successful clients all over the world. We can understand your unique needs. Our team has hands-on experience with the challenges that come with rapid growth and the IT sector. That’s why all of our offerings are built with a tech mindset.

Description:

As a Senior Data Engineer , you will leverage advanced data engineering techniques and analytics to support business decisions for our clients. Your role will involve designing and building robust data pipelines, integrating structured and unstructured data from various sources, and developing tools for data processing and analysis. You will play a pivotal role in managing data infrastructure, optimizing data workflows, and guiding data-driven strategies while working closely with data scientists and other stakeholders.

The impact you will have:

Guide Big Data Transformations: Lead clients through the implementation of comprehensive big data projects, including the development and deployment of innovative big data and AI applications.

Ensure Best Practices: Guarantee that Databricks best practices are applied throughout all projects to maintain high-quality service and successful implementation.

Facilitate Technical Sessions: Conduct technical workshops, discovery sessions, and design meetings to gather and define customer requirements for both new and ongoing strategic initiatives.

Support Project Management: Assist the Professional Services leader and project managers with estimating efforts and managing risks within customer proposals and statements of work.

Architect Complex Solutions: Design, develop, deploy, and document complex customer engagements, either independently or as part of a technical team, serving as the technical lead and authority.

Enable Knowledge Transfer: Facilitate the transfer of knowledge and provide training to team members, customers, and partners, including the creation of reusable project documentation.

Contribute to Consulting Excellence: Share expertise with the consulting team and offer best practices for client engagement, enhancing the effectiveness and efficiency of other teams.

What we look for:

Minimum qualifications:

Educational Background: Bachelor’s degree in Computer Science, Information Technology, or a related field (or equivalent experience).

Experience:

• 4+ years of experience as a Data Engineer, with proficiency in at least two major cloud platforms Azure (Mandate) and AWS or GCP (Optional)

• Proven experience in designing, developing, and implementing comprehensive data engineering solutions using Databricks, specifically for large-scale data processing and integration projects

• Demonstrated expertise in developing scalable streaming and batch solutions using cloud-native components.

• Proven ability to perform data transformation tasks, including cleansing, aggregation, enrichment, and normalization, utilizing Databricks and related technologies.

• Experience in applying DataOps principles and implementing CI/CD and DevOps practices within data environments to optimize development and deployment workflows.

Technical Skills:

• Expert-level proficiency in Spark Scala, Python, and PySpark.

• In-depth knowledge of data architecture, including Spark Streaming, Spark Core, Spark SQL, and data modeling.

• Hands-on experience with various data management technologies and tools, such as Kafka, StreamSets, and MapReduce.

• Proficient in using advanced analytics and machine learning frameworks, including Apache Spark MLlib, TensorFlow, and PyTorch, to drive data insights and solutions.

Databricks Specific Skills:

• Extensive experience in data migration from on-premises to cloud environments and in implementing data solutions on Databricks across cloud platforms (AWS, Azure, GCP).

• Skilled in designing and executing end-to-end data engineering solutions using Databricks, focusing on large-scale data processing and integration.

• Proven hands-on experience with Databricks administration and operations, including notebooks, clusters, jobs, and data pipelines.

• Experience integrating Databricks with other data tools and platforms to enhance overall data management and analytics capabilities.

Preferred qualifications:

Certifications:

• Certification in Databricks Engineering (Professional)
• Microsoft Certified: Azure Data Engineer Associate
• GCP Certified: Professional Google Cloud Certified.
• AWS Certified Solutions Architect Professional