Staff Data Engineering Specialist

TouchTunes•Schaumburg, IL

2d•Hybrid

About The Position

At Touchtunes, your work matters. We are seeking a highly skilled and experienced Staff Data Platform Engineer to lead the design, development, and optimization of our data platform. This role is ideal for someone who thrives at the intersection of cloud architecture, big data engineering, and enabling AI/ML capabilities at scale. You will partner closely with data scientists, analysts, DevOps, and engineering teams to drive scalable, secure, and high-performing data solutions.

Requirements

Deep expertise in Databricks (clusters, jobs, Delta Lake, Unity Catalog, notebooks).
Proficiency in Python and PySpark for developing large-scale data processing jobs.
Advanced SQL skills, including complex joins, window functions, CTEs, and performance tuning.
Hands-on experience with Jenkins for CI/CD automation in data/ML workflows.
Solid understanding of DataOps/MLOps practices, including version control, testing, monitoring, and deployment of data pipelines and models.
Experience with orchestration tools such as Airflow, dbt, or similar.
Familiarity with data security, compliance, and governance frameworks.
Strong problem-solving and communication skills; ability to lead cross-functional technical discussions.

Nice To Haves

Familiarity with AI development tools and environments such as Cursor, and other modern code generation, debugging, or co-piloting platforms.
Experience with containerization and orchestration (e.g., Docker, Kubernetes).
AWS or Databricks certifications are a plus

Responsibilities

Architect and build scalable data platforms using AWS services such as S3, Glue, Lambda, Redshift, EMR, and CloudWatch.
Design and optimize end-to-end ETL/ELT pipelines using Databricks, PySpark, Python, and SQL to support batch and real-time data workflows.
Define, build, and maintain data models and warehouse structures optimized for analytics and ML workloads.
Implement and maintain CI/CD pipelines for data workflows and ML models using Jenkins, Git, and other DevOps tools.
Experience building and supporting real-time data pipelines using tools such as Kafka, Kinesis, or Structured Streaming.
Drive the adoption of DataOps and MLOps best practices, ensuring robust testing, observability, monitoring, and rollback strategies.
Partner with machine learning engineers to enable scalable model training, deployment, and monitoring pipelines.
Establish and enforce data quality, governance, security, and cataloging standards (e.g., Unity Catalog).
Evaluate and recommend new tools and frameworks that enhance the scalability and reliability of the data ecosystem.
Mentor junior engineers, promote engineering excellence, and participate in architectural decision-making.

Benefits

Hybrid Work Environment: Hybrid schedule with 50% work-from-home and in-office time, with the ability to work anywhere in the world for up to 2 months per year.
Financial Wellness: Annual performance bonus, long-term company bonus, 401k matching, life insurance.
Comprehensive Benefits: Competitive health insurance and disability coverage, a Lifestyle Spending Account, access to telemedicine, and an unlimited sick days policy.
Professional Development: Continuous hands-on learning with access to e-learning platform, tuition reimbursement, and peer mentorship.
Accessibility: An inclusive workplace designed to accommodate people with disabilities.

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