Data Engineer
3 hours ago
We are looking for a highly skilled Data Engineer to design, build, and maintain robust data systems and pipelines that transform raw data into actionable insights. The ideal candidate has deep experience in data engineering, cloud technologies (Azure, Databricks), and advanced SQL and Python programming.
Youll be working closely with cross-functional teams including data scientists, analysts, BI developers, and IT architects to ensure data accuracy, scalability, and security across all platforms.
Key Responsibilities
- Design, develop, and maintain data pipelines and data integration frameworks that support business and analytics initiatives.
- Analyze and organize raw data from multiple internal and external sources.
- Build and optimize ETL workflows and data processing systems using Databricks and Azure Cloud services.
- Conduct complex data analysis to identify trends, patterns, and insights.
- Prepare data for predictive and prescriptive modeling.
- Ensure high levels of data quality, security, and reliability across all systems.
- Collaborate with cross-functional teams to understand business requirements and deliver data-driven solutions.
- Document data processes, maintain data dictionaries, and support governance initiatives.
- Continuously evaluate and implement new tools and best practices to improve data efficiency and performance.
Qualifications
- Bachelors degree in Computer Science, Information Technology, or related field (Masters is a plus).
- 5 - 10 years of experience as a Data Engineer or in a similar role.
- Advanced hands-on experience with SQL, Python (or Scala), and Databricks.
- Strong knowledge of Azure Cloud Databases and resource management.
- Proficiency with data modeling, data warehousing, and ETL design.
- Experience with Apache Spark, Delta Lake, and related big data frameworks.
- Familiarity with Salesforce, SAP, Oracle, or Genesys is an advantage.
- Data engineering certifications (e.g., Databricks Certified Data Engineer, Azure Data Engineer Associate) are highly preferred.
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