Company:
Mitsubishi Chemical America, Inc.Job Description:
Senior Data Engineer
Are you passionate about building modern, scalable data platforms that power enterprise analytics? We're looking for a Senior Data Engineer to play a key role in the global implementation and ongoing evolution of our Databricks data platform. This is an exciting opportunity to shape the foundation of our enterprise data strategy while mentoring a growing team of engineers and partnering with stakeholders around the world.
What You'll Do
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.
Define and evolve the Databricks platform architecture, including lakehouse design, data integration patterns, governance, security, performance, reliability, and cost optimization.
- 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.
What We're Looking For
We're seeking an experienced Data Engineer who combines deep technical expertise with strong communication and collaboration skills.
Required Qualifications
- 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).
- At least 5 years of hands-on experience specifically in Databricks development and architecture, including designing, building, optimizing, and supporting production-grade lakehouse solutions.
- 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.
Preferred Qualifications
- Current Databricks certification is a highly important qualification. Strong preference will be given to candidates holding the Databricks Certified Data Engineer Professional certification; the Databricks Certified Data Engineer Associate certification is also strongly valued.
- Experience with Spark, Kafka, or other distributed processing frameworks.
- Experience with DevOps and CI/CD practices.
- Experience supporting machine learning and AI data initiatives.
Why Join Us?
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
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.
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