[Hiring] Senior Cloud Data Engineer @CAI

Role Description

We are seeking a Senior Cloud Data Engineer who will manage the existing cloud data platform to make it more scalable, reliable, and cost efficient. This position will be full-time and remote.

What You’ll Do

• Analyze and understand existing data warehouse implementations to support migration and consolidation efforts.
• Reverse-engineer legacy stored procedures (PL/SQL, SQL) and translate business logic into scalable Spark SQL code within Databricks notebooks.
• Design and develop data lake solutions on AWS using S3 and Delta Lake architecture, leveraging Databricks for processing and transformation.
• Build and maintain robust data pipelines using ETL tools with ingestion into S3 and processing in Databricks.
• Collaborate with data architects to implement ingestion and transformation frameworks aligned with enterprise standards.
• Evaluate and optimize data models (Star, Snowflake, Flattened) for performance and scalability in the new platform.
• Document ETL processes, data flows, and transformation logic to ensure transparency and maintainability.
• Perform foundational data administration tasks including job scheduling, error troubleshooting, performance tuning, and backup coordination.
• Work closely with cross-functional teams to ensure smooth transition and integration of data sources into the unified platform.
• Participate in Agile ceremonies and contribute to sprint planning, retrospectives, and backlog grooming.
• Triage, debug and fix technical issues related to Data Lakes.
• Maintain and manage code repositories like Git.

Qualifications

• 8–12 years of experience in data engineering, data warehousing, or big data platform development.
• 5+ years of hands-on experience with Databricks including Spark, Delta Lake, and performance optimization.
• 4+ years of experience designing and implementing cloud-based data lake or lakehouse architectures on Databricks.
• Strong expertise in Spark technologies including Spark SQL, PySpark, or Scala.
• Advanced SQL and PL/SQL skills with the ability to interpret and refactor legacy stored procedures.
• Strong understanding of data modeling techniques including Star Schema, Snowflake, and modern Lakehouse modeling approaches.
• Proficiency in at least one programming language (Python, Scala, Java).
• Hands-on experience with data modeling and warehouse design principles.
• Experience designing enterprise-scale ETL/ELT pipelines and ingestion frameworks.
• Strong understanding of performance tuning, partitioning strategies, and cost optimization for large-scale data platforms.
• Experience implementing CI/CD pipelines and DevOps practices for data engineering workflows.
• Bachelor’s degree in computer science, Information Technology, Data Engineering, or related field.
• Experience working in Agile environments and contributing to iterative development cycles.

Requirements

• Databricks Professional or Associate Cloud Certification.
• Experience with enterprise data governance, metadata management, and data catalog platforms.

Company Description

CAI is a global services firm with over 9,000 associates worldwide and a yearly revenue of $1.3 billion+. We have over 40 years of excellence in uniting talent and technology to power the possible for our clients, colleagues, and communities. As a privately held company, we have the freedom and focus to do what is right—whatever it takes. Our tailor-made solutions create lasting results across the public and commercial sectors, and we are trailblazers in bringing neurodiversity to the enterprise.