Senior Data Engineer

My client is looking for a Senior Data Engineer to join a growing technology organization and play a key role in building and scaling its modern cloud data platform. NO Recruiters, AGENCIES, C2C, Etc. This is a Full Time direct placement with my client. Strongly prefer candidate lives in CST or EST timezones.

This is a hands-on engineering role for someone who enjoys building production-grade data solutions—not simply maintaining existing pipelines. You’ll take complex data initiatives from design through deployment and help create the frameworks, standards, and reusable tools that allow the data engineering team to move faster.

You’ll work extensively with Databricks, AWS, Python/PySpark, SQL, and modern Lakehouse architecture, building trusted data products that support analytics, reporting, automation, and emerging AI initiatives.

• What You’ll Do
• Design, build, and maintain scalable batch and incremental data pipelines using Databricks and AWS
• Develop and extend layered lakehouse architectures for raw, refined, and curated data
• Build and optimize analytical data models, including dimensional models
• Integrate data from APIs, business applications, relational databases, and other operational systems
• Handle schema changes, incremental loads, late-arriving data, and imperfect source data
• Write clean, tested, well-documented Python/PySpark and SQL
• Develop reusable frameworks, utilities, and engineering patterns
• Own data initiatives from design and development through testing, deployment, monitoring, and ongoing improvement
• Implement data-quality checks, reconciliation, validation, and remediation processes
• Build monitoring, logging, alerting, and reliability processes around production pipelines
• Troubleshoot complex data and pipeline issues and perform root-cause analysis
• Optimize Spark workloads and cloud resources with performance and cost in mind
• Partner with engineering, product, analytics, and business stakeholders to translate requirements into reliable data solutions
• Mentor other data engineers through code reviews, technical guidance, and knowledge sharing
• Contribute practical, hands-on feedback to the evolution of the organization's data architecture and engineering standards
• Develop and maintain datasets and supporting structures for analytics and AI/ML applications
• What We’re Looking For
• 7+ years of experience in data engineering or analytics engineering
• At least 2 years operating at a senior level, leading significant data initiatives
• Strong hands-on experience with Databricks and/or Apache Spark
• Strong PySpark, Python, and SQL skills
• Experience with Delta Lake and Spark workload optimization
• Experience building data solutions on AWS, including services such as S3, IAM, RDS, Glue, or comparable technologies
• Experience with lakehouse or other layered data architectures
• Strong analytical data modeling skills, including dimensional modeling
• Experience working with relational/OLTP systems and incremental or CDC-based data ingestion
• Strong software engineering fundamentals, including Git, testing, code review, and CI/CD
• Experience with data quality, monitoring, observability, and production support
• Experience with orchestration tools such as Databricks Workflows, Airflow, or comparable platforms
• Understanding of data security, access controls, encryption, masking, and sensitive-data handling
• Strong communication skills and the ability to explain technical concepts to non-technical stakeholders
• A Plus
• Experience with Unity Catalog or similar data-governance platforms
• Azure or other cloud experience
• Data Vault or other history-preserving modeling approaches
• Experience supporting AI/ML data requirements
• Experience working in highly regulated or security-conscious environments

• This is an opportunity to join a high-growth technology environment where data engineering is a strategic function.
• You’ll have the opportunity to:
• Own meaningful projects from beginning to end
• Work with a modern cloud data stack
• Influence engineering standards and best practices
• Build scalable infrastructure rather than simply maintain legacy systems
• Work alongside experienced technical leaders
• Help create the data foundation supporting analytics, automation, and AI
• Make a visible impact as the organization continues to scale

If you’re a senior data engineer who enjoys building, solving difficult data problems, and having real ownership over what you create, we’d like to hear from you.