Databricks Data Engineer with Azure, PySpark, Kafka and end-to-end automation of data engineering pipelines.
Self healing pipeline, streaming pipelines, automating pipelines and Databricks Certified
Description:
We are seeking a highly skilled Databricks Data Engineer to support the Retail Spine initiative, working with a wide range of retail datasets to design, build, and optimize scalable data solutions. This role requires deep hands-on expertise in Databricks and the ability to contribute immediately by developing new pipelines while enhancing existing data workflows.
The ideal candidate brings extensive experience building end-to-end data engineering pipelines with CDC (Change Data Capture) capabilities, and thrives in a fast-paced Azure-based environment leveraging Databricks, PySpark, and Kafka streaming.
Key Responsibilities
- Design, build, and optimize end-to-end ETL/ELT pipelines using Databricks and Apache Spark (PySpark).
- Develop and maintain scalable data solutions on Microsoft Azure, leveraging Databricks, Delta Lake, and Kafka streaming.
- Build robust pipelines with Change Data Capture (CDC) to support incremental data processing and real-time/near real-time data needs.
- Work across both new pipeline development and enhancement of existing pipelines, quickly understanding current codebases to deliver improvements.
- Integrate and process data from diverse sources including:
- Flat files, XML, JSON, SQL Server and JDBC systems, Kafka topics, APIs, MQ, Unity Catalog volumes and other enterprise platforms.
- Implement data quality frameworks, including writing technical data quality rules and quarantining error records.
- Apply canonical data modeling techniques, including SCD Type 1 and Type 2 implementations.
- Ensure high levels of data reliability, performance, scalability, and monitoring across all workflows.
- Automate workflows using Databricks Workflows and CI/CD pipelines (GitHub), focusing on reuse, efficiency, and standardization.
- Adhere to ADUSA architecture, governance, and security standards.
- Collaborate with developers, architects, and product owners, and engage with stakeholders, source teams, and downstream consumers as needed.
- Participate actively in Agile/Scrum ceremonies and deliver high-quality solutions within defined timelines.
Required Qualifications
- Extensive hands-on experience with Databricks, with ability to contribute from day one.
- Proven experience building end-to-end data engineering pipelines with CDC capabilities.
- Strong proficiency in PySpark and SQL (required); Python experience is a plus.
- Experience working in Microsoft Azure cloud environments.
- Knowledge of:
- Distributed data processing frameworks
- Streaming technologies (Kafka)
- Data modeling (SCD Type 1 & Type 2)
- Experience integrating data from multiple structured and unstructured data sources.
- Familiarity with GitHub and CI/CD pipelines for version control and deployment.
- Strong understanding of data architecture, performance optimization, and pipeline scalability.
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Data Bricks Engineer employer: V-Soft Consulting Group, Inc.
As a leading employer in the tech industry, we offer Dotnet Developers an exceptional work environment that fosters innovation and collaboration. Our commitment to employee growth is evident through continuous learning opportunities and a supportive culture that values diverse perspectives. Located in a vibrant city, our office provides access to a dynamic tech community, ensuring that you are at the forefront of industry advancements while enjoying a healthy work-life balance.
Contact Details:
V-Soft Consulting Group, Inc. Recruitment Team
