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About
Data Engineer
to build and manage our data infrastructure. The ideal candidate will be an expert in writing complex SQL queries, designing efficient database schemas, and developing ETL/ELT pipelines. You will ensure data is accurate, accessible, and optimized for performance to support business intelligence, analytics, and reporting needs. Key Responsibilities Database Design & Management:
Design, develop, and maintain relational databases (e.g. SQL Server, ProgressSQL, Oracle) and cloud-based data warehouses. Strategic SQL and Data Engineering : Develop sophisticated, optimized SQL queries, stored procedures, and functions to process and analyze large, complex datasets for actionable business insights. Data Pipeline Automation & Orchestration: Help build, automate, and orchestrate ETL/ELT workflows utilizing SQL, Python, and cloud-native tools to integrate and transform data from diverse, distributed sources. Performance Optimization:
Tune queries and optimize database schema (indexing, partitioning, normalization) to improve data retrieval and processing speeds. Data Integrity & Security:
Ensure data quality, consistency, and integrity across systems. Implement data masking, encryption, and role-based access control (RBAC). Documentation:
Maintain technical documentation for database schemas, data dictionaries, and ETL workflows. Required Skills and Qualifications Education:
Bachelor’s degree in computer science, Information Systems, or a related field. SQL Mastery:
5+ years of experience with advanced SQL (window functions, CTEs, query optimization). Database Expertise:
Deep understanding of relational database management systems (RDBMS) and data modeling techniques. Cloud Platforms:
Demonstrated experience with Azure Data Services and other data warehouse technologies. Programming:
Proficiency in Python for scripting and data manipulation. ETL Tools:
Familiarity with tools like SSIS or Azure Data Factory. Soft Skills:
Strong analytical thinking, 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 (e.g., Microsoft Certified: Azure Data Engineer Associate, Google Professional Data Engineer). Typical Work Environment Tools Used:
SQL IDEs (DBeaver, SSMS), Cloud Consoles, Git, Jira, SSIS. Industry:
Leasing. Salary is $130-$140k
Languages
- English
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