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, 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.
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