Data Engineer

Summary

We are seeking a highly skilled 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, Progress SQL, 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.

All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, disability, national origin, or veteran status