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We are looking for a mid-level Data Engineer, experienced with building data pipelines using Python and Airflow for structured data and relational databases. The ideal candidate is a self-directed learner, takes ownership of the pipelines they build, and cares about data quality as much as feature delivery.





Key Responsibilities:

Own our data pipelines, including maintenance and adding new features.
Take charge of data integrity and completeness, including writing and maintaining tests.
Improve process efficiency and optimize runtime performance.
Own schema design and evolution across our data pipelines.

we are looking for a Data Operations Team Lead.
The Data Engagement team is the connective link between GTM and R&D/Product organizations. The team leads customer and prospect data initiatives using internal tools, and drives product improvements based on patterns and issues analysts identify in their day-to-day work.
What you'll do:
Own execution of the team's initiatives - ensuring efforts are properly resourced, tracked, and delivered within required timeframes.
Play a key role in prioritizing data resources across company-wide efforts, working closely with stakeholders across R&D, Product, Customer Success, and Sales.
Lead and develop a multidisciplinary team of highly skilled analysts.
Build strong partnerships with Product and CS leaders, acting as their trusted data advisor to help achieve shared business objectives.

As a Senior Data Scientist , you will be an integral part of our Machine Learning and AI team. The role is hands-on and impact-driven, focusing on building, improving, and delivering machine learning models that directly support business goals.

Responsibilities
Design and deploy production ML systems that drive automated business decisions (pricing, bidding, resource allocation)
Build end-to-end ML pipelines - from data ingestion and model training to serving, monitoring, and incident response
Translate ambiguous business problems into rigorous mathematical frameworks and own them from conception to production impact
Conduct rigorous experimentation (A/B testing, causal inference, uplift modeling) to measure and improve model performance
Maintain and improve real-time models that adapt to incoming data and feedback signals
Mentor junior team members on ML best practices and production standards

As a hands-on individual contributor, you will act as the primary technical expert for the marketing department when data discrepancies or tracking failures occur (e.g., missing conversions, Meta Ads signal drops, or AppsFlyer event mismatches). This position requires a proactive professional who uses SQL and data warehouse environments to identify and resolve anomalies before they impact reporting.

This is a dedicated technical specialist role focused entirely on deep ownership of data infrastructure and troubleshooting, without people-management responsibilities.

Responsibilities
Production Support & Troubleshooting

Own the end-to-end resolution of tracking and signal-delivery incidents (detection, root cause analysis, remediation, and documentation).
Diagnose data discrepancies across three distinct delivery paths: client-side GTM tags, Server-to-Platform CAPI, and reverse ETL.
Address and resolve brand- or country-specific tracking constraints, including regulatory and consent requirements.
Data Quality & Analysis

Conduct regular audits of event and conversion data across major platforms (Google Ads, Meta Ads, GA4, AppsFlyer, TikTok, and programmatic partners) to prevent attribution distortions.
Utilize SQL within Snowflake to validate that events sent via CAPI and reverse ETL match system specifications.
Document technical incidents and resolutions in clear, actionable reports for both technical and non-technical stakeholders.
AppsFlyer & GTM Ownership

Manage configurations and serve as the primary subject-matter expert for AppsFlyer and Google Tag Manager (both client-side and server-side) across all brands.
Partner with the internal GA4 team on cross-functional data issues (without holding direct responsibility for GA4 configuration).

a Senior Data Analyst position to join the BI Team, with a passion for technology, to solve unique problems within our measurements.
Responsibilities
Function as the data authority in the Monetization domain - performing ad-hoc research and analysis on the company's rich data to support unique and strategic business questions.
Define, analyze, and monitor KPIs and OKR metrics to continually improve company products.
Analyze large, complex data sets to address strategic and operational business questions.
Actively take part in building and maintaining our AI Driven-BI Agentic Architecture.
Build dashboards and visualizations to answer key questions for the company's in-house various teams, specifically for the Monetization Team.
Perform qualitative, quantitative, and statistical analysis.
True passion for understanding data and finding Insights.
Provide actionable recommendations and conclusions from data to shape features and future product road maps.

About The Position
Design, build, and maintain scalable data pipelines and infrastructure entirely within GCP
Own data solutions end-to-end, from architecture and design through to production delivery
Build and maintain custom connectors to advertising platforms including Google Ads, Meta (Facebook) Marketing API, and other ad platforms
Design and implement data warehouse structures with a deep focus on performance, scalability and usability
Continuously investigate and evaluate new GCP native tools and services, assessing their fit, building proof of concepts, and driving adoption where it makes sense
Set up and configure orchestration and transformation frameworks (such as Airflow and dbt) within the GCP environment
Collaborate closely with backend engineers to ensure data infrastructure aligns with product and system needs
Contribute to data science initiatives and bring genuine curiosity to analytical use cases
Monitor, troubleshoot, and continuously improve the reliability and performance of existing data systems
Define technical standards and best practices for the data platform
Build and maintain data dashboards and reports to surface insights for stakeholders, primarily using Looker Studio.

Required Data Scientist Team Lead
Description
About Us:
We are bootstrapped and has been profitable since day one. We built one of the most efficient programmatic acquisition engines on the planet: processing billions of ad decisions a day, generating terabytes of live behavioral data, and turning it into margins most SaaS companies would kill for.
At the core of that engine is a team of data scientists and ML engineers running tens of billions of sub-second predictions a day, deciding in milliseconds which impression is worth buying and what its worth.
Now were taking everything weve learned about how people move through the web and putting it into our most innovative consumer product yet: Ace AI, an AI-native browser already reaching millions of people, built to simplify and improve everyday online life with the help of AI.
This is a rare opportunity: a category that hasnt meaningfully changed in over a decade, and a profitable company with the data and the acquisition engine to win it on its own terms.
Come build it with us.
What Youll Do:
Mentor a team of extremely talented and success-hungry data scientists.
Initiate and manage cutting-edge projects from inception to delivery, including developing structured and automated solutions.
Lead the data strategy: be responsible for planning, prioritizing, and building the right data solutions to support business needs.
Apply your scientific knowledge and creativity to analyze large volumes of diverse data and develop algorithmic solutions and models to solve complex problems.
Identify and propose data science and algorithmic solutions for various product initiatives.
Use your excellent communication skills, both written and verbal, to explain technical concepts and analysis implications to senior leaders, and influence cross-functional teams to improve performance.
Partner with other departments (i.e. Management, R&D, Product) to support decision making.

We are looking for an experienced Senior Data Engineer to join our Data team. In this role, you will lead and strengthen our Data Team, drive innovation, and ensure the robustness of our data/analytics platforms.
A day in the life and how youll make an impact:
Design and develop high-performance Data Pipelines and ETL processes to support diverse business needs.
Work closely with Product, Business Intelligence, Sales and other teams to integrate data solutions, ensuring seamless alignment and collaboration across functions.
Continuously improve our data analytics platforms, optimizing system performance and ensuring robust, reliable data infrastructure.
Oversee the entire data lifecycle, from infrastructure setup and data acquisition to detailed analysis and automated reporting, driving business growth through data-driven insights.
Implement robust data quality checks, monitoring mechanisms, and data governance policies to maintain data integrity and security, troubleshooting and resolving any data-related issues efficiently.

We are looking for an Engineering Director to join our engineering leadership team, reporting directly to the VP of Engineering.
In this leadership role, you will own & manage a multi-disciplinary Engineering group spanning AIgo, full-stack, AIOps, QA, and data - accountable for delivery, people, and business outcomes. You will work closely with a Principal Product Manager who sets direction, and directly manage a Product Owner embedded in your team.
Heres what youll be doing:
Own your Engineering group delivery end-to-end - planning, prioritization, dependencies, risks, and outcomes.
Drive accountability: commitments are kept, blockers surfaced early, quality is non-negotiable.
Directly manage all engineers and the Product Owner in your squad, supported by functional guilds.
Run 1:1s, give meaningful feedback, support growth, and build a high-accountability team culture.
Provide technical guidance in close partnership with Principal Architects and senior engineers.
Stay engaged enough to earn trust, spot risk early, and make informed trade-off calls.
Connect your squads work to business outcomes. Always ask why it matters before deciding what to build.
Participate actively in leadership discussions on roadmap, resourcing, and strategy.

Were looking for a Director of Data to lead our evolving Data organization. This is a unique opportunity for an experienced technical leader who thrives at the intersection of leadership and execution. In this role, youll shape the future of our data platform and infrastructure while remaining closely connected to the technology, architecture, and innovation that drive our business forward.
Why Join Us:
Lead a strategically important Data organization during a transformative phase of growth and evolution.
Shape the technical vision, operating model, and future direction of Data Engineering and Data Infrastructure.
Work hands-on with modern data technologies, AI-driven workflows, and emerging platforms while operating at a senior leadership level.
Influence critical company-wide initiatives and partner closely with leaders across R&D, Product, Finance, Support, and GTM.
Join a culture that values ownership, technical excellence, continuous learning, and meaningful impact.
Key Responsibilities
Lead our Data organization in its next phase, driving a lean, high-performing, and highly technical operating model.
Own the technical vision, architecture, and execution across Data Engineering and Data Infrastructure.
Directly manage and mentor a multidisciplinary team, fostering growth, accountability, and engineering excellence.
Provide strong hands-on technical leadership, guiding architectural decisions, reviewing designs, and driving execution on critical initiatives.
Partner with stakeholders across the organization to deliver scalable data products and platforms that support business and product needs.
Drive modernization of our data ecosystem, balancing proven data technologies with emerging approaches in AI, automation, and modern data platforms.
Lead strategic initiatives involving critical infrastructure, platforms, and investments, ensuring scalability, reliability, and operational efficiency.
Champion best practices in data engineering, platform reliability, observability, and operational excellence.

We are looking for a Senior Data & AI Engineer to join a new and growing Data & AI function. You'll work hands-on with models and data architecture, with direct impact on both product-facing AI capabilities and internal data infrastructure. This is a deeply technical role: you'll take ML models from research through production, design scalable pipelines, and collaborate closely with R&D and Product to solve real security problems with AI.
Responsibilities:
Design and implement data architecture, pipelines, and governance foundations
Develop and deploy ML models into production (not just POCs), focusing on areas like vulnerability detection, attack emulation, and security insights
Own model lifecycle end to end: research and experimentation, production deployment, monitoring, and iteration
Partner with Product and R&D to identify and execute high-impact AI use cases within our platform
Evaluate build vs. buy vs. fine-tune decisions for AI capabilities
Define and maintain data quality standards and access policies.

This is a unique opportunity to build and lead a strategic Data & AI capability within a leading consulting firm, shaping its vision, offerings, team, and market presence. The role combines business leadership, solution architecture, and client engagement, helping organizations leverage modern Data & AI platforms to drive transformation and innovation.
Job description
Lead and expand Databricks practice, including strategy, capability development, team growth, and go-to-market initiatives.
Design and oversee enterprise-scale Data & AI solutions, including Lakehouse architectures, data modernization programs, and AI-driven platforms.
Build trusted relationships with senior stakeholders, lead business development efforts, and drive complex technology engagements.
Lead the successful delivery of large-scale Data & AI projects while mentoring and developing high-performing teams.