Hillenbrand
Data Engineering Technical Lead
Remote Data Engineering role with clear candidate location fit.
PostedJun 15, 2026
Eligible countries1 accepted country
Seniority signalSenior
Work settingRemote
Accepted candidate locations
India
Role overview
Data Engineering Technical Lead
Requirements and responsibilities
Readable role content extracted into sections for faster review.
Work You’ll Do:
- Serve as the primary technical lead and escalation point for enterprise data engineering initiatives
- Bridge business requirements, architectural standards, and engineering implementation
- Partner with business analysts, architects, BI teams, DevOps, and data engineers to support successful solution delivery
- Interpret and clarify technical implementation requirements for data engineering teams
- Guide implementation decisions across Databricks pipelines, transformations, and data models
- Review engineering implementations for consistency, scalability, maintainability, and alignment to standards
- Support troubleshooting and root cause analysis for data quality issues, failed pipelines, performance concerns, and production defects
- Act as L1/L2 support lead for enterprise data platform operational issues
- Perform lineage and downstream impact analysis for data model and pipeline changes
- Guide implementation of reusable engineering patterns, medallion architecture, and gold-layer datasets
- Coordinate defect triage, release support, deployment validation, and production stabilization activities
- Support adoption of engineering standards, CI/CD processes, governance controls, and operational best practices
- Mentor and guide data engineers on technical implementation approaches and enterprise standards
- Drive consistency across engineering teams, platforms, and data products
- Document technical patterns, implementation standards, operational procedures, and support processes
Basic Qualifications:
- 12+ years of experience in data engineering, analytics engineering, BI engineering, or related technical roles and graduate in Engineering / Technology or on related field.
- Strong understanding of enterprise data warehousing, dimensional modeling, and modern data platform concepts
- Hands-on experience with Databricks, Spark, Delta Lake, SQL, and Python
- Experience supporting enterprise-scale data platforms and engineering teams
- Strong troubleshooting, root cause analysis, and technical problem-solving skills
- Experience reviewing engineering implementations and guiding technical delivery
- Experience with data lineage, dependency analysis, and downstream impact assessment
- Ability to translate business and reporting requirements into practical engineering guidance
- Strong communication and collaboration skills across business and technical teams
- Knowledge of DevOps, CI/CD, release management, and deployment processes
Preferred Qualifications:
- Experience supporting Power BI semantic models and enterprise reporting environments
- Experience with Azure cloud data technologies including Azure Data Factory and Azure Data Lake
- Experience with metadata management, governance, or catalog platforms
- Experience operating within large, complex, multi-business-unit enterprise environments
- Exposure to AI-assisted development, automation, or engineering productivity tools
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