Cloud Data Engineering Lead
5 days ago
Oliver James Associates is a leading recruiter of top data talent. As a Cloud Data Engineering Lead, you will have the opportunity to work with a dynamic technology-driven organization.
About the Role
We are seeking a Senior Data Engineer with strong expertise in Azure Databricks to join our client's team. The ideal candidate will bring hands-on experience with Azure Databrick, Delta Lake, and Apache Spark, along with strong coding skills in Python or Scala.
Key Responsibilities
- Data Architecture & Engineering:
- Develop and maintain end-to-end data pipelines using Azure Databricks, Delta Lake, and other Azure data services.
- Architect and implement scalable, high-performance data solutions to support business needs.
- Apply best practices for data modeling, using both relational and dimensional techniques.
- Platform Development and Ownership:
- Act as the technical lead for the organization's cloud-based analytics platform, encompassing the data warehouse, data lake, and operational data stores.
- Partner with cross-functional stakeholders to ensure the platform supports analytics, reporting, and decision-making requirements.
- Mentorship and Collaboration:
- Guide and mentor junior engineers to foster technical growth within the team.
- Collaborate with business analysts, architects, and other team members to define and deliver data solutions.
- Data Quality and Transformation:
- Design and implement ETL/ELT workflows to transform raw data into clean, usable datasets.
- Ensure data quality by implementing validation, monitoring, and governance practices.
- Cloud Technology SME:
- Stay informed on emerging cloud technologies and incorporate them into the organization's data strategy.
Required Qualifications
- Azure Cloud Expertise:
- Deep knowledge of Azure Databricks, Azure Data Factory, Azure Data Lake, Azure SQL, and related Azure services.
- Experience in ETL frameworks and data pipeline orchestration.
- Programming and Data Processing:
- Proficiency in Python and PySpark for developing scalable data solutions.
- Advanced knowledge of SQL for querying and transforming data.
- Experience with distributed computing frameworks such as Apache Spark.
- Data Modeling and Transformation:
- Experience designing and implementing data models using dimensional and relational approaches.
- Strong knowledge of data transformation techniques for building analytics-ready datasets.
- Automation and DevOps Integration:
- Experience with DevOps, version control, and CI/CD pipelines.
Experience
- Bachelor's degree in Computer Science, Data Science, or a related field.
- 8+ years of experience in data engineering, with a focus on cloud-based solutions.
- Proven experience delivering enterprise-scale data platforms, including data lakes and warehouses.
- Exposure to end-to-end software development lifecycle (SDLC), from design to deployment.
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