Posted today · be early
Data Engineering Technical Lead
Hillenbrand
IndiaremotePosted today
Skill Required
Data-EngineeringTechnical-LeadData-Platform-EngineeringEnterprise-Data-EngineeringAnalytics-EngineeringTech-Lead-Data-EngineeringData-Engineering-LeadLead-Data-EngineeringLead-Data-EngineerData-Engineering-Team-LeadSenior-Lead-Data-EngineeringSenior-Data-Engineering-LeaderLead-Data-Engineer-JobsData-Tech-LeadTeam-Lead-(Data-Engineering)Data EngineerTechnical Leaddata engineeringEngineeringData Warehousingtroubleshootingrelated fieldCD pipelinesAzureDatabricksSystem AdministrationautomationPower BIanalyticsSparkPythondesignDevOpsCI/CDUnityCloudSQLandCICDAIFulltime
Key highlights
- 12+ years of data engineering or related experience required
- Hands‑on experience with Databricks, Spark, Delta Lake, SQL, and Python
- Experience supporting enterprise‑scale data platforms and engineering teams
- Strong troubleshooting and root‑cause analysis capabilities
- Senior technical leadership role with mentorship responsibilities
- Employer is a global industrial leader committed to EEO and accommodations
Role overview
The Data Engineering Technical Lead serves as the senior technical execution lead for the enterprise data engineering environment. This role bridges business intent, architecture, analytics, and engineering implementation to ensure scalable, reliable, and governed data solutions are successfully delivered. The individual will provide day-to‑day technical leadership for data engineers, support implementation decisions, resolve technical ambiguity, guide operational support activities, and help ensure consistency across enterprise data platforms. This role combines strong hands‑on technical expertise with operational leadership, problem‑solving, and the ability to translate business and reporting needs into practical engineering execution.
Responsibilities
- 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
Requirements
- 12+ years of experience in data engineering, analytics engineering, BI engineering, or related technical roles and graduate in Engineering / Technology or 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
Nice to have
- 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
Additional details
- Technical Environment: Databricks; Spark / PySpark; Delta Lake; SQL; Python; Power BI; Azure Data Factory; Azure Data Lake; Unity Catalog / Data Lineage; Azure DevOps; CI/CD Pipelines
- Company: Mold‑Masters, a leading global supplier of hot runners, controllers, auxiliary injection and co‑injection systems, part of Hillenbrand, a global industrial company serving customers in over 100 countries
- EEO Statement: Hillenbrand Inc. provides equal employment opportunities regardless of age, race, color, sex, religion, national origin, disability, sexual orientation, gender identity/expression or veteran status, and offers accommodations for applicants with disabilities
- Posting Origin: Originally posted on Himalayas
