Analytics Engineer Product & Tech · Paris ·

Go Electra; Paris; Sur place; EUR 60 000 - 90 000; Plein temps

Avantages offerts par ce poste

Remote work 2 days/week

Health insurance (Alan)

Meal vouchers Swile

25 vacation days + 12 RTT

SYNTEC benefits

Résumé du poste

Electra is deploying thousands of fast‑charging points across Europe. We are seeking an Analytics Engineer to join our data team to turn raw data into a reliable, self‑service product.

You will co‑own the transformation layer end‑to‑end, including clean models, a consolidated semantic/context layer, and a trustworthy analytics agent for business and product teams.

Qualifications

• Solid SQL and dbt foundations for clean transformation layers.
• Strong data modelling fundamentals to design reusable schemas.
• Experience with modern cloud data warehouses like Snowflake and ELT stacks.
• Interest in designing or governing semantic and context layers.
• Commitment to data testing, monitoring, anomaly detection, and CI/CD.

Responsabilités

• Co‑own the dbt transformation layer across domains with tests and docs.
• Extend and reinforce semantic/context layer; ensure consistent metric definitions.
• Improve analytics agent to answer business questions reliably with guardrails.
• Model new domains and onboard sources (e.g., SAP, electricity costs) into models.
• Harden data quality with monitoring and anomaly detection.
• Contribute to data-platform foundations (Dagster orchestration and Airbyte ingestion).

Connaissances

SQL

dbt

Data modelling

Semantic layer

CI/CD

Data testing

Version control

Outils

Snowflake

Dagster

Airbyte

Omni

Metabase

AWS

Description du poste

What We Do

Founded in 2021 with the ambition to make cities cleaner and quieter, Electra is accelerating the shift to electric mobility by tackling the main barrier: charging.

We are building and operating a network of fast‑charging stations (20 minutes on average) with a seamless and intuitive user experience.

Based in Paris, Lyon, Bordeaux, Nantes, Brussels, Madrid, Zurich, Vienna, Munich, Milan and Amsterdam, our teams aim to deploy 15,000 fast‑charging points by 2030, contributing to Europe’s energy transition.

In just 5 years, we have:

• Deployed +750 stations and 4,000+ fast‑charging points

• Opened offices in several European countries

• Raised over €1B from leading investors and institutions

• Joined French Tech Next40 and won European Scale‑up of the Year 2024

• Grown to a team of 280+ talented people… and we’re just getting started!

Your Mission

Electra is deploying thousands of fast‑charging points across Europe, and almost every decision behind them - where to build, how to price, how the network performs - depends on trustworthy data.

Our centralized data platform already powers reporting and analytics across Finance, Operations, Growth, Energy and more, with a broad catalog of data models and metrics. As we scale, we need one additional Analytics Engineer to help support our growth, tackle new data domains, and reinforce our semantic and context layer.

Your mission is to turn Electra's raw data into a reliable, self‑service product the whole company can trust. You’ll co‑own the transformation layer end to end – clean data models, a consolidated semantic and context layer, and a reliable analytics agent – so that business and product teams all build on the same solid foundation.

We’re open to a range of experience levels, from junior to senior: we care most about fundamentals and trajectory. You’ll have a senior Analytics Engineer and the wider data team to learn from and grow with.

Your Responsibilities

1. Co‑own the dbt transformation layer: design and maintain data models across business domains, with clear ownership, tests and documentation in our hub‑and‑spoke architecture.

2. Extend and reinforce our semantic and context layer: keep metric definitions governed and consistent, expand coverage to new domains, and enrich the business context so every metric is defined once and interpreted the same way – across our BI tools and by our analytics agent.

3. Enhance our analytics agent: shape the semantic and context layer so an LLM‑powered agent can answer business questions accurately, with the guardrails and evaluation that make its answers trustworthy.

4. Model new domains as the business grows: onboard sources like SAP, electricity costs and more into well‑structured, reusable data models.

5. Keep data trustworthy: harden our monitoring and alerting into robust metrics auditing and anomaly detection, so issues surface before stakeholders notice them.

6. Contribute to the data‑platform foundations tied to analytics workloads: orchestration (Dagster) and ingestion (airbyte).

Your Profile

Technical skills

sorted by priority (high to low)

Required

• Solid SQL and dbt foundations, and the drive to build clean, maintainable transformation layers (we expect depth to scale with your experience).

• Solid data modelling fundamentals: you design clean, reusable schemas and know how to turn messy sources into trustworthy marts.

• Comfortable on a modern cloud data warehouse (Snowflake or equivalent) and the surrounding ELT stack.

• A genuine care for metric consistency and clear definitions (hands‑on experience designing or governing a semantic and context layer is a plus).

• You care about reliability and quality: data testing, monitoring, anomaly detection, version control and CI/CD.

Nice‑to‑have

• Data‑quality / observability tooling (Elementary, or similar).

• Orchestration (Dagster or similar) and ingestion tooling (Airbyte or similar).

• BI and self‑service enablement (Omni, Metabase, or similar).

• Building or evaluating LLM‑powered data tools (analytics agents, text‑to‑SQL), including guardrails and eval sets.

• Cloud infrastructure exposure (AWS) and infrastructure‑as‑code.

Mindset

sorted by priority (high to low)

• Trust is the product. You treat correctness and reliability as the deliverable – a metric people can rely on beats a clever model no one trusts.

• Business‑driven. You start from the decision the data needs to support, talk to stakeholders, and model for the consumer, not the pipeline.

• Leverage over one-offs. You’d rather define a metric once and make it reusable than answer the same question ten times. You build foundations others build on.

• Ownership beyond the model. You care what happens downstream: whether the dashboard is right, the alert fired, and the decision was made on good data.

• Collaborative. You partner closely with other data team members, and business teams, and pick things up wherever they need to move.

What Electra Offers You

• A key role in a massive international rollout of Europe’s largest fast‑charging network.

• Opportunities to grow across engineering, operations, and strategy.

• A collaborative and mission‑driven environment.

• Real impact on the energy transition and the future of mobility.

• An attractive compensation package with fixed and variable components (evaluated and paid quarterly).

• Brand‑new offices in the 2nd arrondissement of Paris.

• 2 days of remote work per week.

• Alan health insurance (50% covered by Electra).

• Meal vouchers via Swile card (€10/day, 50% covered by Electra).

• 25 paid vacation days + 12 RTT (reduction of working time) days.

• SYNTEC collective agreement (including vacation bonus, additional leave for special occasions, etc.).

• A quarterly company‑wide event with the entire Electra team.

• Sustainable Mobility Package.

• Access to the company benefits platform (CSE) with numerous perks (culture, sports, etc.).

• Access to a platform dedicated to mental health, supporting your well‑being at work and beyond, including up to 4 sessions per year with certified practitioners, covered by Electra.

Even if your profile doesn't match 100% of every criterion, we encourage you to apply. At Electra, we strive to create an environment where everyone feels comfortable, safe, and free to be themselves.

We are committed to equal opportunities and do not tolerate any discrimination based on religion, cultural background, nationality, gender, sexual orientation, age, or disability.

We value potential, motivation, and a learning mindset just as much as experience.