(Senior) Data Engineer
Full-time
ABB E-mobility
Are you ready to be the owner of data systems that power critical business decisions? Do you thrive when you can turn raw data into reliable pipelines, scalable infrastructure, and insights that drive real impact? If so, we have an exciting opportunity for you. Within ABB E-mobility, we are building a new venture focused on an end-to-end managed offering that brings together hardware, software, and operational excellence into a unified service model. This is a unique opportunity to join a fast-scaling, high-impact business within ABB E-mobility, where you as (Senior) Data Engineer will play a key role in shaping the data platform for our next growth chapter. What You Will Do We are looking for a (Senior) Data Engineer to be our first internal hire in this new venture. Our data platform has been built on Azure Databricks and is live in production. You will own it end-to-end. Note: This is not a role for the faint of heart. You’ll be joining a fast-moving team where priorities shift quickly, challenges come without warning, and solutions rarely exist yet. It will demand grit, speed, and relentless ownership. Your Responsibilities Will Include
- Own our data platform end-to-end, whether it means deciding on the best strategy to ingest a new data source or repairing a broken pipeline at 10 pm (thankfully our pipelines rarely break :))
- Proactively identify data quality issues, pipeline gaps, and business logic inconsistencies before data consumers find them
- Build and maintain data pipelines using Delta Live Tables (DLT) as our core framework, authored in Python and SQL and deployed via Databricks Asset Bundles
- Extend and maintain our custom API ingestion framework (a native Spark Data Source) to onboard new data sources, handling pagination, incremental state, and schema evolution
- Integrate and process streaming data from Azure Event Hubs into our data Lakehouse
- Own data modelling and medallion architecture decisions (Bronze/Silver/Gold), including evolving them as the business grows
- Develop a genuine understanding of the business domain: charging network operations, industry protocols (OCPP, OCPI), billing logic, and how the data is used by our Operations team
- Orchestrate and monitor multi-step jobs end-to-end using Databricks Workflows
- Manage and evolve cloud infrastructure using Terraform on Azure (Event Hubs, ADLS, Key Vault, Unity Catalog, networking) in combination with Databricks Asset Bundles for workspace assets
- Enforce data quality through DLT expectations and SQL alert definitions; own freshness and observability standards for the platform
- Maintain CI/CD pipelines via Azure DevOps
- Contribute to our customer-facing Charging Portal, which currently embeds Databricks dashboards and serves as the foundation for future API endpoints and customer self-service features
- 4–7 years of experience as a Data Engineer or equivalent role
- Strong SQL and PySpark skills, comfortable reasoning about distributed execution, partitioning, and query performance
- Hands-on experience with Databricks, ideally with Delta Live Tables (DLT), Databricks Workflows, and Unity Catalog
- Experience with streaming data architectures (Azure Event Hubs or equivalent)
- Experience building REST API ingestion pipelines: incremental loads, pagination, schema evolution, auth patterns
- Comfortable with cloud infrastructure as code (Terraform preferred, or equivalent)
- Familiarity with CI/CD pipelines (Azure DevOps or equivalent)
- Truly autonomous, able to define your own priorities and make architectural decisions you can defend
- Deeply curious about the business domain, you'll be expected to learn and understand the EV charging industry, protocols, billing flows, etc.
- Strong ownership mentality, you treat production incidents as your personal responsibility
- Comfortable managing shifting priorities and ambiguity
- Fluent in English, with strong written and oral communication skills
Vacancy posted 21 days ago
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