Senior Data Engineer

As a Senior Data Engineer, you'll serve as one of the technical leaders on our Data Platform team, helping design, implement, and optimize enterprise-scale data solutions that enable business intelligence, advanced analytics, and AI initiatives.

In this role, you will:

• Lead the implementation and continued enhancement of our global Databricks data platform.
• Design, build, and optimize scalable ETL/ELT pipelines for structured and semi-structured data.
• Develop modern data models, data warehouses, and data marts to support enterprise analytics.
• Collaborate closely with data scientists, analysts, business partners, and IT teams to translate business requirements into scalable technical solutions.
• Improve data quality, governance, security, and platform reliability.
• Optimize data workflows for performance, scalability, and cost efficiency.
• Provide technical mentorship to junior and mid-level data engineers while helping establish engineering best practices., This is more than a traditional data engineering role-it's an opportunity to help build the next generation of our global data platform.

You'll join a growing Data Platform team where you'll:

• Lead enterprise-wide Databricks initiatives.
• Work alongside a collaborative team while mentoring developing engineers.
• Influence technical direction and engineering best practices.
• Partner with business leaders across Finance, Sales, Supply Chain, Manufacturing, and Corporate functions.
• Help drive digital transformation across a global organization

We're seeking an experienced Data Engineer who combines deep technical expertise with strong communication and collaboration skills., * Bachelor's degree in Computer Science, Engineering, Information Systems, or a related field required

• 5+ years of hands-on experience with SQL and Python.
• 5+ years of experience working with cloud platforms (Azure, AWS, or GCP).
• 5+ years of experience with modern data warehousing technologies such as Databricks, Snowflake, Redshift, or BigQuery.
• Strong experience designing and building enterprise-scale data pipelines and ETL/ELT solutions.
• Solid understanding of data modeling, governance, and security principles.
• Excellent communication skills with the ability to collaborate across technical and business teams., * Databricks Certification.
• Experience with Spark, Kafka, or other distributed processing frameworks.
• Experience with DevOps and CI/CD practices.
• Experience supporting machine learning and AI data initiatives.

The salary range for this position is $110,200-$144,700. Factors such as scope and responsibilities of the position, candidate's work experience, education/training, job-related skills, internal peer equity, as well as market and business considerations may influence base pay offered. This salary will be subject to a geographic adjustment (according to a specific city and state), if an authorization is granted to work outside of the location listed in this posting.