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, 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