Lead Analytics Engineer Job at Spendesk (Paris)

Data Engineering & Analytics Lead

Premium Health is seeking a highly skilled, hands-on Data Engineering & Analytic...

Location

United States , Brooklyn

Salary:

Not provided

Premium Health

Expiration Date

Until further notice

Requirements

Bachelor's degree in Computer Science, Engineering, or a related field. Master's degree preferred
Proven track record and progressively responsible experience in data engineering, data architecture, or related technical roles
healthcare experience preferred
Strong knowledge of data engineering principles, data integration, ETL processes, and semantic mapping techniques and best practices
Experience implementing data quality management processes, data governance frameworks, cataloging, and master data management concepts
Familiarity with healthcare data standards (e.g., HL7, FHIR, etc), health information management principles, and regulatory requirements (e.g., HIPAA)
Understanding of healthcare data, including clinical, operational, and financial data models, preferred
Advanced proficiency in SQL, data modeling, database design, optimization, and performance tuning
Experience designing and integrating data from disparate systems into harmonized data models or semantic layers
Hands-on experience with modern cloud-based data platforms (e.g Azure, AWS, GCP)

Job Responsibility

Collaborate with the CDIO and Director of Technology to define a clear data vision aligned with the organization's goals and execute the enterprise data roadmap
Serve as a thought leader for data engineering and analytics, guiding the evolution of our data ecosystem and championing data-driven decision-making across the organization
Build and mentor a small data team, providing technical direction and performance feedback, fostering best practices and continuous learning, while remaining a hands-on implementor
Define and implement best practices, standards, and processes for data engineering, analytics, and data management across the organization
Design, implement, and maintain a scalable, reliable, and high-performing modern data infrastructure, aligned with the organizational needs and industry best practices
Architect and maintain data lake/lakehouse, warehouse, and related platform components to support analytics, reporting, and operational use cases
Establish and enforce data architecture standards, governance models, naming conventions ,and documentation
Develop, optimize, and maintain scalable ETL/ELT pipelines and data workflows to collect, transform, normalize, and integrate data from diverse systems
Implement robust data quality processes, validation, monitoring, and error-handling frameworks
Ensure data is accurate, timely, secure, and ready for self-service analytics and downstream applications

What we offer

Paid Time Off, Medical, Dental and Vision plans, Retirement plans
Public Service Loan Forgiveness (PSLF)

Fulltime

Lead Analytics Engineer

As a Analytics Engineer in the Data Infrastructure Team at Prolific, you'll be a...

Location

United Kingdom

Salary:

Not provided

Prolific

Expiration Date

Until further notice

Requirements

Expertise in dbt & SQL: Deep experience with dbt and SQL to design, build, and maintain scalable data models
Cloud Technology Knowledge: Strong familiarity with cloud platforms like AWS, GCP etc
Data Accuracy Focus: Passion for ensuring high data quality through tests/assertions and robust documentation
Commercial Acumen: Ability to understand business needs and communicate effectively with non-technical stakeholders
Mentorship Ability: Advocate for best practices in logging and data modeling that supports robust and effective analysis, reporting , and experimentation
Collaboration: Skilled at working cross-functionally and translating complex technical concepts into actionable insights for the business
Process-Driven: Proficiency in designing repeatable and scalable workflows for data transformation

Job Responsibility

Building Data Models: Create complex dbt models, custom macros, and reusable packages. Optimise transformations and implement robust testing strategies to ensure data integrity and model performance
Ownership: Monitoring and maintaining dbt workflow jobs, ensuring smooth data refreshes and up-to-date pipelines.You will also be responsible for data models for BI analytics & company level reporting
Ensuring Data Accuracy: Writing tests and assertions to validate data integrity and consistency across models
Documenting and Standardizing: Creating and maintaining thorough documentation of dbt processes to ensure best practices within the BI team
Translating Complex Data Concepts: Acting as a key communicator, translating technical data issues into understandable business terms for stakeholders
Mentoring Team Members: Supporting junior analysts and data engineers, especially in setting up experimentation platforms and data best practices
Collaborating Across Teams: Working closely with the product, engineering, and BI teams to ensure data infrastructure supports evolving business needs

Analytics Engineer, Product Analytics

As an Analytics Engineer at Airtable, you’ll play a pivotal role in shaping our ...

Location

United States , San Francisco; New York City

Salary:

143600.00 - 177200.00 USD / Year

Airtable

Expiration Date

Until further notice

Requirements

Bachelor’s degree in computer science, data science, mathematics/statistics, or a related field (or related experience)
3–5 years of experience working with data, with at least 1 year partnering with product stakeholders
Curiosity and fluency with AI/LLM tools (ChatGPT, Claude, Cursor, etc.)
Experience in SaaS, consumer tech, or data-driven product environments
Proficiency with SQL and data modeling best practices (e.g., dbt, Databricks, Snowflake, BigQuery)
Experience with BI tools and BI modeling best practices (e.g., Looker, Omni Analytics, Tableau, Mode, Hex)
Understanding of user funnels, retention metrics, and growth analytics
Strong ability to ensure data accuracy, reliability, and consistency
Ability to translate business questions into analytical approaches, interpret results, and communicate actionable insights
Knowledge of product analytics tracking frameworks (e.g., Segment, Amplitude, Mixpanel, GA4) and event taxonomy design

Job Responsibility

Own and maintain core product data pipelines across tools such as dbt, Databricks, Looker, and Omni Analytics, ensuring reliability and scalability
Build and refine dashboards that deliver self-serve, real-time insights for high-priority product areas
Partner with product and engineering teams to define tracking requirements, implement instrumentation, validate data, and deliver launch-specific dashboards or reports
Establish trusted partnerships with product managers, engineers, analysts, and leadership, serving as the go-to resource for product data insights and technical guidance
Lead analytics engineering efforts for high-impact product launches, including documentation of tracking plans, launch pipelines, and post-launch reporting
Participate in or lead cross-functional projects where analytics engineering contributions directly influence product strategy decisions

What we offer

Restricted stock units
Incentive compensation
Comprehensive benefits package

Fulltime

Senior Analytics Engineer

Join Qargo as a Senior Analytics Engineer and turn complex logistics data into c...

Location

Belgium , Ghent

Salary:

Not provided

Qargo

Expiration Date

Until further notice

Requirements

Extensive experience in data analytics, BI engineering, or analytics engineering in a SaaS or data-driven environment
Strong proficiency in SQL, data modelling, and dashboarding tools (Lightdash, Superset, Tableau, Looker, or PowerBI)
Experience with analytics platforms such as Mixpanel and user behavior tracking methodologies is a plus
Proven ability to collaborate effectively with multidisciplinary teams (product, engineering, sales, finance)
Strong analytical and problem-solving skills, with an eye for scalability and data quality
A background in Computer Science, Data Engineering, Statistics, or a related field
A proactive mindset with the ability to take ownership of complex problems and guide them to completion

Job Responsibility

Own and evolve Qargo’s data architecture, ensuring scalable, reliable and high-quality data pipelines
Maintain, extend and optimise our in-app Lightdash dashboards, including operational, financial, and performance insights
Build and refine internal BI dashboards to support data-driven decision-making across departments
Develop account management dashboards that reveal feature adoption, revenue insights, and upsell opportunities
Create product and engineering analytics, including feature usage dashboards using Mixpanel or custom-built tracking solutions
Lead integration-related reporting, providing visibility on integration health, tenant usage, and performance
Build billing and cost-analysis dashboards, including API call cost allocation and tenant-level breakdowns
Mentor team members, set best practices, and raise the bar for analytics engineering within Qargo

What we offer

Real impact and ownership in a growing international scale-up
A supportive and collaborative team culture
Hybrid working setup with flexibility and trust
Opportunities to learn, grow, and expand your technical knowledge
Competitive salary and benefits package

Senior Analytics Engineer, Corporate Strategy

Join us in building the future of finance. Our mission is to democratize finance...

Location

United States , Menlo Park

Salary:

179000.00 - 210000.00 USD / Year

Robinhood

Expiration Date

Until further notice

Requirements

5+ years of experience in Analytics Engineering, Data Engineering, Data Science, or similar field
Strong expertise in advanced SQL, Python scripting, and Apache Spark (PySpark, Spark SQL) for data processing and transformation
Proficiency in building, maintaining, and optimizing ETL pipelines, using modern tools like Airflow or similar
Experience in building polished and performant dashboards using tools like Superset, Looker, Tableau
Strong familiarity with version control (GitHub), CI/CD, and modern development workflows
A strong business acumen around business strategy and competitive landscape
Ability to work in a fast-paced, and highly multi-functional environment

Job Responsibility

Partner cross-functionally with product, engineering, and business teams to scope and deliver high-impact analytics initiatives, from metric definitions to fully automated reporting solutions
Design and maintain reliable, scalable pipelines and data models using modern data tools (e.g., Airflow, Spark), ensuring performance and accuracy at scale
Lead end-to-end development of analytics products—from ingestion to visualization—that meet critically important business, product, and regulatory needs
Build internal frameworks and tooling to make high-quality data more accessible and actionable across the organization
Support competitive benchmarking efforts, providing technical expertise for competitive intelligence and contextualizing Robinhood’s performance relative to peers
Advocate for customers by helping establish best practices in how we measure, interpret, and act on customer feedback

What we offer

Performance driven compensation with multipliers for outsized impact, bonus programs, equity ownership, and 401(k) matching
100% paid health insurance for employees with 90% coverage for dependents
Lifestyle wallet - a highly flexible benefits spending account for wellness, learning, and more
Employer-paid life & disability insurance, fertility benefits, and mental health benefits
Time off to recharge including company holidays, paid time off, sick time, parental leave, and more
Exceptional office experience with catered meals, events, and comfortable workspaces

Fulltime

Senior Analytics Engineer II

Articulate is looking for a Sr. Analytics Engineer to join our amazing Data team...

Location

United States

Salary:

137700.00 - 206500.00 USD / Year

Articulate

Expiration Date

Until further notice

Requirements

8+ years of experience in data or analytics roles
At least 5 years in analytics engineering, preferably within a fast-paced tech company or data-driven organization
Expert in end-to-end data workflows, from data collection to analysis and presentation, with most expertise in data modeling
Confident in translating raw data to reusable, business-friendly data models
Proven experience owning and leading the creation of reliable, flexible data models in an enterprise data warehouse
Expertise in SQL (writing and analyzing complex queries)
Expertise in Data Build Tool (dbt)
Expertise in Looker/Tableau (defining data models and measures)
Experience building semantic layers using dbt, Looker, or Snowflake’s semantic tables
Ability to write complex SQL, run ad-hoc data discovery, and build data models

Job Responsibility

Provide flexible, trustworthy data models by transforming data from multiple sources with DBT, testing for quality, deploying to visualization tools such as Looker or Tableau, and publishing documentation
Collaborate directly with stakeholders to define problems and determine requirements for a solution
Set and maintain best practices for data models and processes, including project architecture and QA
Proactively identify gaps or design flaws in our data models, and bring recommendations for how to fix them
Own documentation of our tools and data, both for our team and for external users
Lead discovery on data tools and infrastructure, including setting goals for tooling, continuous analysis of existing tooling, and exploring new tools and features we may adopt
Participate as a technical leader in project planning, helping to create well-defined tasks to address data initiatives
Mentor more junior members of the data team
Represent the data team in some technical architecture and planning conversations
Identify and share data risks and dependencies in these contexts

What we offer

Bonus eligible
Robust suite of benefits

Fulltime

Director, Data Engineering & Analytics

We are seeking a proven Data and Analytics leader to run our data team. This rol...

Location

United States , Washington, DC

Salary:

165000.00 - 295625.00 USD / Year

Arcadia

Expiration Date

Until further notice

Requirements

Expert Data & Analytics leader with demonstrated experience processing and analyzing large-scale datasets (billions of records)
Deep expertise with Snowflake as a data platform, including performance optimization, cost management, and architecting for scale
Hands-on experience with modern data stack: dbt for transformation, Hex for analytics, and Fivetran/Airbyte for data ingestion
Have built and led Data & Analytics teams at high-growth SaaS companies, specifically those dealing with high-volume data processing
Experience with utility data, billing systems, or similar high-volume transactional data is highly valued
12+ years in the workforce with significant experience in data-intensive environments
Top-notch technical skills covering both data and quantitative techniques: data facility, descriptive analytics, and predictive modeling
SQL and Python are a must, with demonstrated ability to write optimized queries for large-scale data processing
Experience with data governance, security, and compliance in handling sensitive customer data

Job Responsibility

Build, lead, and scale a successful data organization
Oversee the processing and analysis of several million utility bills per month, ensuring data pipeline reliability, accuracy, and scalability
Ensure data quality and that we are building our products to give our customers the insight they need
Build a multi-year strategy around data infrastructure, enterprise data modeling, and processing capabilities
Build a framework for data investments that ensures we are appropriately balancing R&D with products that deliver strong return on investment
Lead the optimization and evolution of our Snowflake-based data architecture to handle exponential data growth
Own the enterprise unified data model and architecture that will power all of Arcadia’s applications and use cases

What we offer

competitive benefits and equity component to the package

Fulltime

Data & Analytics Engineer

As a Data & Analytics Engineer with MojoTech you will work with our clients to s...

Location

United States

Salary:

90000.00 - 150000.00 USD / Year

MojoTech

Expiration Date

Until further notice

Requirements

3+ years of experience in Data Engineering, Data Science, Data Warehousing
Strong experience in Python
Experience building and maintaining ETL/ELT pipelines, data warehouses, or real-time analytics systems
BA/BS in Computer Science, Data Science, Engineering, or a related field or equivalent experience in data engineering or analytics
Track record of developing and optimizing scalable data solutions and larger-scale data initiatives
Strong understanding of best practices in data management, including sustainment, governance, and compliance with data quality and security standards
Commitment to continuous learning and sharing knowledge with the team

Job Responsibility

Work with our clients to solve complex problems and to deliver high quality solutions as part of a team
Collaborating with product managers, designers, and clients, you will lead discussions to define data requirements and deliver actionable insights and data pipelines to support client analytics needs

What we offer

Performance based end of year bonus
Medical, Dental, FSA
401k with 4% match
Trust-based time off
Catered lunches when in office
5 hours per week dedicated to self-directed learning, innovation projects, or skill development
Dog Friendly Offices
Paid conference attendance/yearly education stipend
Custom workstation
6 weeks parental leave

Fulltime

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Lead Analytics Engineer

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