Description We are seeking a highly skilled Data Engineer to design, build, and manage our data infrastructure. The ideal candidate is an expert in writing complex SQL queries, designing efficient database schemas, and developing ETL/ELT pipelines. This role ensures data accuracy, accessibility, and performance optimization to support business intelligence, analytics, and reporting initiatives.
Key ResponsibilitiesDatabase Design & Management- Design, develop, and maintain relational databases, including SQL Server, PostgreSQL, and Oracle, as well as cloud-based data warehouses.
Strategic SQL & Data Engineering- Develop advanced, optimized SQL queries, stored procedures, and functions to process and analyze large, complex datasets and deliver actionable business insights.
Data Pipeline Automation & Orchestration- Build, automate, and orchestrate ETL/ELT workflows using SQL, Python, and cloud-native tools to integrate and transform data from diverse, distributed sources.
Performance Optimization- Tune SQL queries and optimize database schemas through indexing, partitioning, and normalization to improve data retrieval and processing performance.
Data Integrity & Security- Ensure data quality, consistency, and integrity across systems.
- Implement data masking, encryption, and role-based access control (RBAC).
Documentation- Maintain comprehensive technical documentation, including database schemas, data dictionaries, and ETL workflows.
Requirements Required Skills & Qualifications
- Bachelor's degree in Computer Science, Information Systems, or a related field
- 5+ years of experience with advanced SQL, including window functions, CTEs, and query optimization
- Strong understanding of relational database management systems (RDBMS) and data modeling techniques
- Demonstrated experience with Azure Data Services and other data warehouse technologies
- Proficiency in Python for scripting and data manipulation
- Familiarity with ETL tools such as SSIS or Azure Data Factory
- Strong analytical, problem-solving, and communication skills
Nice to Have
- Experience with NoSQL databases (Cosmos DB, MongoDB)
- Experience with big data frameworks (Apache Spark, Kafka)
- Relevant certifications, such as Microsoft Certified: Azure Data Engineer Associate or Google Professional Data Engineer
Typical Work Environment
- Tools Used: SQL IDEs (DBeaver, SSMS), Cloud Consoles, Git, Jira, SSIS
- Industry: Leasing
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