Senior Data Engineer - Azure Databricks Platform
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Role & Responsibilities
- The role will be responsible for taking technical ownership of key workstreams on EnerMech's Azure Databricks data platform, operating across the full platform stack: data modelling and pipeline development in Databricks, the underlying Azure infrastructure, and the CI/CD, DevOps and DataOps practices that keep the platform reliable, secure and scalable.
- Working for our Enterprise Business Systems (EBS) function in the Mumbai Shared Service Centre, the role holder operates with a high degree of autonomy, makes and documents architectural decisions, resolves complex platform issues, and is a technical point of contact for the global EBS Team, and business stakeholders.
- Key reponsibilities will include:
- Design, build, quality and reliable operation of assigned workstreams on the Azure Databricks data platform, from scoping through to production deployment.
- Integrity of the medallion data model (bronze/silver/gold) for assigned data domains, ensuring data is modelled, validated, documented and certified for downstream reporting and analytics.
- Build and optimise Delta tables and materialized views, with attention to performance at scale.
- Design and implement data quality frameworks (preferably DQX or equivalent), including quarantine/error handling and validation against data contracts.
- Define job-specific compute configurations appropriate to each workload, balancing performance and cost.
- Contribute to and troubleshoot Terraform-managed infrastructure (networking, storage, Key Vaults, Managed DevOps Pools, Dev Centers).
- Own and maintain Azure DevOps build and release pipelines, variable groups/libraries, and repository security, permissions and branch policies.
- Support environment-level Azure configuration, including subscription-level access, RBAC for user and pipeline (service principal) identities, and Terraform state backend management across multiple storage accounts and environments.
- Operate autonomously across a workstream, from scoping through to production deployment.
- Use AI-assisted tooling to support day-to-day development, validating outputs against authoritative sources (architecture decisions, technical leads, documentation) before acting on them.
- Communicate clearly with technical and non-technical stakeholders, including across time zones with colleagues in the UK, Americas, Middle East and Asia Pacific.
- The Requirements
- Essential
- Bachelor's degree in Computer Science, Engineering, Information Systems or a related discipline, or equivalent practical experience.
- Typically 6+ years in data engineering, including 3+ years hands-on with Azure Databricks in production.
- Demonstrated ownership of medallion architecture design and data modelling.
- Implemented data quality frameworks and data contracts in production.
- Implemented PII protection (masking, tokenisation or access tiering) across environments.
- Platform engineering experience: diagnosing infrastructure issues, not just consuming platform services.
- Track record of autonomous delivery, including direct stakeholder engagement.
- Databricks Certified Data Engineer Associate (minimum).
- Desirable
- Databricks Certified Data Engineer Professional.
- Microsoft AZ-400: Designing and Implementing Microsoft DevOps Solutions.
- Multi-environment Azure networking (VNet peering, DNS zone design, NAT Gateway).
- Migrating or standing up CI/CD pipelines, incl. introducing pipeline templates/standards.
- Governance and identity patterns (e.g. Entra ID, RBAC scoping).
- Applying regulatory frameworks (e.g. GDPR) to data platform design.
- Shared service centre or global delivery model experience, ideally in energy or industrial services.
Qualifications
- Bachelor's degree in Computer Science, Engineering, Information Systems or a related discipline, or equivalent practical experience.
About EnerMech
Specialist provider of integrated energy and industrial solutions.
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