Data Engineer

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 Responsibilities

Database 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.

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