Senior Data Engineer - Python and Terraform skills at Shift Technology

Paris, Ile-de-France, France -

Full Time

Start Date

Immediate

Expiry Date

29 May, 26

Salary

0.0

Posted On

28 Feb, 26

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, Terraform, Generative AI, Agentic AI, Predictive AI, SaaS, Distributed Systems, APIs, C#, .NET Core, MS SQL Server, Spark, Azure Data Factory, Databricks, GoodData, ETL/ELT

Industry

Software Development

Description

Shift is the leading AI platform for insurance. Shift combines generative, agentic, and predictive AI to transform underwriting, claims, and fraud and risk - driving operational efficiency, exceptional customer experiences and measurable business impact. Trusted by the world's leading insurers, Shift delivers AI when and where it matters most, at scale and with proven results. Our culture is built on innovation, trust, and a drive to transform the insurance industry through our SaaS platform. We come from more than 50 different countries and cultures and together we are creating the future of insurance. Our Engineering team lies at the core of the value we offer to our customers. We solve complex problems not only within our squads but also by working collaboratively with other teams across the organization. We’re reshaping the way data drives decision-making by building powerful, scalable software and data platforms. Whether you're passionate about distributed systems, building APIs, or enabling data-driven insights, you'll find exciting opportunities here. Our tech stack includes .NET Core (C#), Python, MS SQL Server, Spark, Azure Data Factory , Databricks,GoodData ,terraform and more. We are also progressing towards distributed data systems on cloud platforms, with exciting challenges in both batch and real-time processing. WHAT YOU'LL DO Drive end-to-end data architecture design for scalable and resilient systems. Design, implement, and maintain robust ETL/ELT pipelines. Own and optimize Apache Spark-based pipelines (debugging, hardening, tuning, performance optimization). Translate business requirements into scalable data models and warehouse schemas. Improve pipeline performance, reliability, scalability, and cost efficiency. Lead or contribute to POCs and new technology adoption initiatives. Ensure best practices in data governance, quality, observability, and monitoring. Work closely with cross-functional teams (Analytics, ML, Product, Platform). Mentor and support junior engineers, providing technical guidance and code reviews. Take ownership of infrastructure provisioning and unblock yourself when needed. Actively Document and Diagram the technical design and architecture. WHAT YOU BRING 8+ years experience, Tech Lead experience is a plus. Drive software architecture, understand the data model/ETL mapping, contribute to new tech adoption (POCs), and mentor peers. Apache Spark a must, with experience debugging, hardening and optimising pipelines 3+ years of SQL database, CosmosDB 3+ years experience in custom ETL design, implementation and maintenance 3+ years experience with Data Modeling Strong understanding of: Distributed data systems Data warehousing concepts Batch and event-driven processing Performance and scalability troubleshooting Hands-on experience with: Databricks DBT Infrastructure as Code (Terraform, ARM, Bicep, etc.) Azure data services (Event Hub, Service Bus, ADLS, Synapse, etc.) Experience provisioning infrastructure and setting up data pipelines independently. Bonus Experience with stores: DBT , Analytical tools, feature store, vector database, Nice to have: OLAP db, GraphDB, / SQL mesh (Niche) HIRING PROCESS Talent Acquisition interview - 30 minutes Hiring Manager interview - 45 minutes Technical Screening with an Architect - 45 to 60 minutes Second Technical Screening with a Tech Lead or Data Engineer - 45 to 60 minutes Final Round with Hiring Manager - 60 minutes #LI-RH1 #LI-HYBRID To support our permanent, full time employees at every stage of their careers and lives, we provide a competitive total rewards and benefits package. Here are the global benefits we’d like to highlight: Flexible remote and hybrid working options Competitive Salary and a variable component tied to personal and company performance Multiple Learning and Development opportunities, including Focus Fridays, a half-day each month to focus on learning and personal growth Generous PTO and paid holidays Mental health benefits 2 MAD Days per year (Make A Difference Days for paid volunteering) Additional benefits may be offered by country, based on your eligibility - ask your recruiter for more information. Intern and Apprentice positions may receive some of these benefits - ask your recruiter for more details. At Shift we strive to be a diverse and inclusive workforce. We welcome applications from and hire people who will contribute to the diversity of our company, without regard to race, color, religion, marital status, age, national or ethnic origin, physical or mental disability, medical condition, pregnancy, genetic information, gender identity or expression, sexual orientation, or other non-merit criteria. Shift Technology is committed to providing reasonable accommodations for qualified individuals with disabilities in our application and employment process. Should you require accommodation, please email accommodation@shift-technology.com and we will work with you to meet your accessibility needs. Please be aware of scammers and only trust correspondence that comes from emails ending in "shift-technology.com". We will never do initial outreach to you via Whatsapp/Text/SMS, never ask for banking information or personal identification numbers (ex. Social Security Number) as part of our recruitment process. Shift Technology does not accept unsolicited CVs from recruiters or employment agencies in response to the Shift Technology Careers page or a Shift Technology social media post. Any unsolicited CVs, including those submitted directly to hiring managers, are deemed to be the property of Shift Technology.

Responsibilities

Drive end-to-end data architecture design for scalable and resilient systems, including designing, implementing, and maintaining robust ETL/ELT pipelines using technologies like Apache Spark. Responsibilities also involve translating business requirements into scalable data models, optimizing pipeline performance, and ensuring data governance and observability.