Senior Data Engineer, Shift Technology

Python and Terraform Skills

Salary not provided

+ Variable component tied to personal and company performance

SQL

Terraform

Azure

Spark

dbt

Azure Databricks

Senior and Expert level

Paris

AI-driven insurance fraud solution

Be an early applicant

AI-driven insurance fraud solution

501-1000 employees

B2BArtificial IntelligenceInternal toolsInsuranceAnalyticsSaaSAutomation

Be an early applicant

Salary not provided

+ Variable component tied to personal and company performance

SQL

Terraform

Azure

Spark

dbt

Azure Databricks

Senior and Expert level

Paris

501-1000 employees

B2BArtificial IntelligenceInternal toolsInsuranceAnalyticsSaaSAutomation

Company mission

To revolutionise the policyholder experience through wide-ranging products that apply AI and advanced data science to key insurance processes.

Job

Company

Role

Who you are

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)

What the job involves

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
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

Application 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

Our take

The global insurtech market is projected to grow substantially given the increased demand for insurance service digitisation, projected market expansion, and developments in technology that have made it easier to buy and process claims. Insurtech helps create new avenues that large insurance companies have less incentive to pursue, such as offering social insurance and customised policies for clients.

In January 2021, Shift Technology introduced the Shift Insurance Suite to help the insurance industry apply AI-based decision automation and optimisation technology solutions. This addresses critical processes across the insurance policy lifecycle, and helps insurers to achieve faster, more accurate claims and policy resolutions.

Shift Technology is focusing on continuous deployment in the UK and the US, whilst exploring opportunities in Singapore, as it attempts to become an international player in the market. However, it must stave off a number of major competitors to do so, including Quantemplate, Slice and Neos.

Kirsty

Company Specialist at Welcome to the Jungle

Insights

Top investors

-1% employee growth in 12 months

Glassdoor (4.2)

Company

Funding (last 2 of 7 rounds)

May 2021

$220m

SERIES D

Mar 2019

$61.7m

SERIES C

Total funding: $321.7m

Company benefits

Flexible remote and hybrid working options
Competitive Salary and a variable component tied to personal and company performance
Company equity
Generous PTO and paid holidays
Parental leave opportunities
Extensive mental health benefits provided via our global Employee Assistance Program
Paid volunteering time - 16 hours annually

Company HQ

Bercy, Paris, France

Leadership

Jeremy Jawish

(Co-Founder & CEO)

Experience in fraud detection solution development for AXA in 2011, and as an FICC Strategist for Goldman Sachs in 2012.

Eric Sibony

(Co-Founder & CSO)

PhD in machine learning from 2012-2016, and has been CSO since 2013.

David Durrleman

(Co-Founder & Fellow Engineer)

Experience as a Fixed Income Strategist for Goldman Sachs between 2008-2013.

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