Lead Data Engineer

Managing your social networks has never been so simple!

Who are we?
French leader in social media management, Agorapulse is deployed in 15 countries and supports +31,000 users worldwide.
So what are we doing exactly? We allow agencies, companies and marketers to manage their social networks in one spot while proving real impact to their marketing efforts and bottom line. Programming your content, editing statistical reports, calculating the ROI of the social media strategy and interacting with the audience and the team from a single platform for all social networks: Facebook, Twitter, Instagram, LinkedIn, YouTube, Google My Business, TikTok, Pinterest, Threads and soon Bluesky.
Some numbers
We now have more than 155 enthusiastic employees across the globe with our headquarters in Paris. Our semi-remote organization allows us to have employees all around the world.
What we can offer as Lead Data Engineer
Agorapulse is transitioning from a centralized to an embedded data team model to enhance the impact of data analysts by integrating them into specific teams. This pivotal role will report to the CTO, serving as both a leader for the data chapter and a hands-on contributor.
The Lead Data Engineer is responsible for maintaining high standards of best practices across teams, ensuring knowledge sharing, and driving the adoption of cutting-edge solutions, particularly around large language models (LLMs).
This role combines technical expertise, leadership, and strategic vision, playing a vital part in advancing Agorapulse's data capabilities and leveraging AI/ML innovations to improve internal processes and product features.
The Data organization:
Agorapulse's data team is transitioning to an embedded model:
Data Analysts: Alberto: Embedded with Marketing, Sales, and RevOps.
Arnaud: Embedded with Product, Customer Care, and Finance.

Data Engineer (Eric): Responsible for data ingestion (Segment, Fivetran, Airbyte), observability (Airflow), and alerting.
Your responsibilities:
Data Engineering (40%)
Design the vision and execute the technical processes for integrating data from companies that we will acquire. This encompasses data ingestion, data transformation, data analysis, and data activation.
Maintain the existing modern data stack, keep it up to date. Monitor and optimize the data stack for cost and efficiency. Change what you believe will make it better. Ensure proper tool usage and improve processes to streamline operations.
Contribute to our dbt pipeline, to make sure that the business has data they need, and ensure that you know the data that teams are using.
Participate to data engineering delivery on a daily basis. Check alerts and fix them.

LLM Innovation (30%)
Lead the discovery, testing, and implementation of LLMs for both internal operations and product features.
Support product and development teams in leveraging LLMs effectively and efficiently.
Management / Leadership (30%)
Lead the data chapter (4 people) by organizing weekly meetings to share news, insights, and best practices.
Foster collaboration and alignment across data analysts and engineers while maintaining team cohesion.
Manage the Data Engineer: hold weekly 1:1 meetings, provide guidance, and offer technical mentorship.
Key Outcomes
Drive cohesive collaboration within the embedded data team.
Provide mentorship and technical challenges to data chapter members.
Promote the adoption of ML/LLM solutions for impactful operations and product innovation.
Maintain alignment with the company's strategic data vision.
The data stack
Ingestion: Segment, Fivetran, Airbyte.
Data Warehouse: BigQuery.
Transformations: dbt, orchestrated with Airflow (Google Cloud Composer).
BI: Metabase.
ML: Langsmith platform with OpenAI, Gemini, and Bedrock models at scale.
About you
Must haves
Experience: 6+ years in data engineering.
Experience with LLMs (GenAI) in production is a plus.
Technical Skills: Proficiency in Python, SQL, and the modern data stack.
Languages: Fluency in French and English.
Qualities We Value
Problem Solver: Sees challenges as opportunities for improvement.
Doer: Takes initiative and experiments with new ideas.
Technician: Hands-on technical expertise in data and ML tools.
Visionary: Clear understanding of ideal data flows and long-term strategy.
Communicator: Shares vision and fosters enthusiasm within the team.
Team Player: Invests in colleagues' growth and contributes to a positive team environment.
Proactive: Takes ownership to improve processes and outcomes.
Efficient: Delivers quickly, iterates based on feedback, and values progress over perfection.
Why Join us
Enjoy a scale-up environment with a great work-life balance.
Evolve in a SaaS, B2B, Tech, and international context.
An exceptional working atmosphere (you can look at our Glassdoor).
Collaborate with amazing colleagues and be part of an enthusiastic team.
The next steps
The aim is to give you the opportunity to get to know the future key members of your team as well as possible. Between each stage, you will always be accompanied by our Talent Acquisition team.
Call with Capucine, Talent Acquisition Specialist (30 min)
Interview with Juliette, hiring manager (40 min)
A case study, with an on-site presentation (1h30)
A culture fit interview with our CEO (40 min)
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