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Tech Lead – Data Engineer (Databricks)
Job Location:
Job Location:
Cincinnati, OH - USA
Monthly Salary:
Not provided by the employer
Monthly Salary:
Posted:
29 September 2026 (11 hours ago)
Posted:
Application Deadline:
27 December 2026
Application Deadline:
Vacancies:
1 Vacancy
Vacancies:
Job Summary
At Staffworxs we dont just connect talent we power transformation. Headquartered in Frisco TX with teams in Bengaluru and Hyderabad we combine global reach with deep expertise. Our Digital & Data Analytics practice drives growth and innovation for some of the worlds top brands who continue to retain us as their trusted partner. If youre ready to make an impact youre in the right place.
Job Details:
Tech Lead Data Engineer (Databricks)
Location: Cincinnati OH
Work model: Onsite / hybrid; local candidates strongly preferred. Non-local candidates must be willing to work onsite in Cincinnati.
Duration: 12 months Contact
Responsibilities:
Role overview
We are seeking a hands-on highly capable Lead Data Engineer / Databricks Tech Lead to lead the design build modernization and ongoing evolution of customer-data platforms supporting a large-scale retail and digital ecosystem.
This person will be the onsite technical lead work independently with business and technology stakeholders and provide technical direction to both onsite & offshore engineering teams. The ideal candidate is fundamentally strong in data engineering and distributed data systems has deep Databricks expertise communicates clearly with both technical and non-technical partners and can turn ambiguous business needs into scalable production-ready data solutions.
Must Haves for this role:
Key responsibilities
Required qualifications
Preferred qualifications
Staffworxs is an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive workplace for all employees regardless of race color religion gender sexual orientation national origin age disability or veteran status.
Job Details:
Tech Lead Data Engineer (Databricks)
Location: Cincinnati OH
Work model: Onsite / hybrid; local candidates strongly preferred. Non-local candidates must be willing to work onsite in Cincinnati.
Duration: 12 months Contact
Responsibilities:
Role overview
We are seeking a hands-on highly capable Lead Data Engineer / Databricks Tech Lead to lead the design build modernization and ongoing evolution of customer-data platforms supporting a large-scale retail and digital ecosystem.
This person will be the onsite technical lead work independently with business and technology stakeholders and provide technical direction to both onsite & offshore engineering teams. The ideal candidate is fundamentally strong in data engineering and distributed data systems has deep Databricks expertise communicates clearly with both technical and non-technical partners and can turn ambiguous business needs into scalable production-ready data solutions.
Must Haves for this role:
- Strong recent production-level Databricks experience.
- Strong hands-on PySpark and SQL capability.
- Ability to independently design troubleshoot and deliver data-platform solutions.
- Proven technical-lead experience - not only project coordination.
- Strong verbal communication and stakeholder-facing maturity.
- Experience guiding a distributed engineering team.
- Availability to work onsite in Cincinnati Ohio.
Key responsibilities
- Lead the technical design architecture and implementation of large-scale data engineering solutions on Databricks.
- Design and build scalable reliable and maintainable data pipelines data models workflows and data products for customer loyalty coupon retail and digital-platform data.
- Establish and evolve a modern Databricks Lakehouse architecture including data ingestion transformation orchestration quality validation serving layers and operational monitoring.
- Develop production-grade data pipelines using PySpark SQL Delta Lake and Databricks-native capabilities.
- Lead modernization initiatives for customer-data and analytics platforms including assessment target-state architecture migration planning implementation validation and production rollout.
- Define and enforce data engineering standards for coding testing CI/CD code review documentation observability performance optimization and cost management.
- Drive best practices for data quality schema evolution data lineage metadata governance access control and privacy-sensitive customer data.
- Work closely with application engineering product analytics business architecture security and infrastructure teams to gather requirements and align delivery plans.
- Translate business and customer-data use cases into logical and physical data models scalable pipelines and reusable platform components.
- Act as the onsite technical owner and point of escalation for the offshore Data Engineering team; provide clear work breakdown technical guidance code reviews prioritization and mentoring.
- Prepare effort estimates technical designs implementation plans risks dependencies and rollout approaches for data engineering initiatives.
- Troubleshoot complex data performance pipeline reliability and production-support issues.
- Communicate progress risks architecture decisions and delivery status effectively to stakeholders and leadership.
- Champion continuous improvement across engineering practices operational maturity delivery velocity and platform reliability.
Required qualifications
- 10-15 years of hands-on experience in Data Engineering software engineering data platforms or a closely related technical discipline.
- 3 years of strong production-level experience with Databricks.
- Deep hands-on expertise with PySpark Spark SQL Python SQL distributed processing and performance tuning.
- Strong experience designing and implementing end-to-end data pipelines including batch and ideally streaming data workloads.
- Practical experience with Delta Lake Delta tables partitioning file optimization schema evolution data quality checks and data lifecycle management.
- Experience designing data lakehouse data warehouse or enterprise customer-data platform architectures.
- Strong understanding of data modeling including dimensional modeling curated data products and customer/entity-level data design.
- Experience with cloud-based data engineering preferably Azure and Azure Databricks.
- Experience with CI/CD source control code review automated testing deployment automation and environment promotion for data pipelines.
- Strong ability to independently assess ambiguous requirements make sound technical decisions and drive complex work to completion.
- Demonstrated experience leading engineers technically mentoring team members and coordinating distributed or offshore teams.
- Excellent verbal and written communication skills including the ability to explain technical concepts architecture tradeoffs and delivery risks to diverse stakeholders.
Preferred qualifications
- Experience supporting customer loyalty coupon retail eCommerce payment customer-experience or marketing data domains.
- Experience building customer 360 identity-resolution segmentation personalization offer promotion or analytics data products.
- Experience with Databricks Workflows Unity Catalog Delta Live Tables Auto Loader Structured Streaming and/or Databricks Asset Bundles.
- Experience with Azure Data Factory Azure DevOps ADLS Gen2 Event Hubs Kafka or similar cloud data services.
- Familiarity with data governance PII handling data masking role-based access control auditability and enterprise data compliance requirements.
- Experience leading modernization programs involving legacy data warehouses ETL platforms or fragmented customer-data environments.
- Background in large enterprise retail digital commerce consumer-data or high-volume transactional environments.
Staffworxs is an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive workplace for all employees regardless of race color religion gender sexual orientation national origin age disability or veteran status.
Required Experience:
Staff IC
