Join Exadel as a Senior Data Engineer (Snowflake) and build scalable apps that make an impact. You’ll explore new tech, work with the latest tools, and thrive in a fast-moving Agile team.

Why Join Exadel 

We’re an AI-first global tech company with 25+ years of engineering leadership, 2,000+ team members, and 500+ active projects powering Fortune 500 clients, including HBO, Microsoft, Google, and Starbucks.

From AI platforms to digital transformation, we partner with enterprise leaders to build what’s next.

What powers it all? Our people are ambitious, collaborative, and constantly evolving.

About the Client  

An education services provider offering online and campus-based post-secondary education, primarily serving military personnel, veterans, and public service communities. The organization delivers degree and certificate programs across disciplines such as nursing, health sciences, business, IT, and liberal arts. In addition to its headquarters in West Virginia, the customer operates facilities and partner institutions across the United States.

What You’ll Do  

• Design, implement, and maintain scalable data pipelines using Snowflake, Coalesce.io, Airbyte, and SQL Server/SSIS, with some use of Azure Data Factory
• Build and maintain dimensional data models to ensure high-quality, structured data for analytics and reporting
• Implement Medallion architecture in Snowflake, managing bronze, silver, and gold layers
• Collaborate with teams using Jira for task tracking and GitHub for code repository management
• Ensure reliable ETL processes, data transformations, and data integration workflows
• Help improve data modeling practices and address weaknesses in dimensional modeling

What You Bring  

• Hands-on experience with Snowflake, Coalesce.io, Airbyte, SQL Server/SSIS, and Azure Data Factory
• Strong understanding of Medallion architecture and dimensional data modeling
• Practical experience in building ETL pipelines and transforming data for analytics
• Familiarity with Jira and GitHub for collaborative work
• Strong analytical and problem-solving skills, with ability to collaborate across teams
• Minimum 4-hour overlap with US Eastern Time

Nice to Have

• Exposure to Power BI
• Experience with Salesforce data integration
• Background in higher education / ed-tech domains

English level 

Intermediate/Upper-Intermediate

Legal & Hiring Information 

• Exadel is proud to be an Equal Opportunity Employer committed to inclusion across minority, gender identity, sexual orientation, disability, age, and more
• Reasonable accommodations are available to enable individuals with disabilities to perform essential functions
• Please note: this job description is not exhaustive. Duties and responsibilities may evolve based on business needs

Your Benefits at Exadel  

Exadel benefits vary by location and contract type. Your recruiter will fill you in on the details.

• International projects
• In-office, hybrid, or remote flexibility
• Medical healthcare
• Recognition program
• Ongoing learning & reimbursement 
• Well-being program
• Team events & local benefits 
• Sports compensation 
• Referral bonuses 
• Top-tier equipment provision

Exadel Culture

We lead with trust, respect, and purpose. We believe in open dialogue, creative freedom, and mentorship that helps you grow, lead, and make a real difference. Ours is a culture where ideas are challenged, voices are heard, and your impact matters.

Join Exadel as a Senior Data Engineer (Snowflake) and build scalable apps that make an impact. You’ll explore new tech, work with the latest tools, and thrive in a fast-moving Agile team.

Why Join Exadel 

We’re an AI-first global tech company with 25+ years of engineering leadership, 2,000+ team members, and 500+ active projects powering Fortune 500 clients, including HBO, Microsoft, Google, and Starbucks.

From AI platforms to digital transformation, we partner with enterprise leaders to build what’s next.

What powers it all? Our people are ambitious, collaborative, and constantly evolving.

About the Client  

An education services provider offering online and campus-based post-secondary education, primarily serving military personnel, veterans, and public service communities. The organization delivers degree and certificate programs across disciplines such as nursing, health sciences, business, IT, and liberal arts. In addition to its headquarters in West Virginia, the customer operates facilities and partner institutions across the United States.

What You’ll Do  

• Design, implement, and maintain scalable data pipelines using Snowflake, Coalesce.io, Airbyte, and SQL Server/SSIS, with some use of Azure Data Factory
• Build and maintain dimensional data models to ensure high-quality, structured data for analytics and reporting
• Implement Medallion architecture in Snowflake, managing bronze, silver, and gold layers
• Collaborate with teams using Jira for task tracking and GitHub for code repository management
• Ensure reliable ETL processes, data transformations, and data integration workflows
• Help improve data modeling practices and address weaknesses in dimensional modeling

What You Bring  

• Hands-on experience with Snowflake, Coalesce.io, Airbyte, SQL Server/SSIS, and Azure Data Factory
• Strong understanding of Medallion architecture and dimensional data modeling
• Practical experience in building ETL pipelines and transforming data for analytics
• Familiarity with Jira and GitHub for collaborative work
• Strong analytical and problem-solving skills, with ability to collaborate across teams
• Minimum 4-hour overlap with US Eastern Time

Nice to Have

• Exposure to Power BI
• Experience with Salesforce data integration
• Background in higher education / ed-tech domains

English level 

Intermediate/Upper-Intermediate

Legal & Hiring Information 

• Exadel is proud to be an Equal Opportunity Employer committed to inclusion across minority, gender identity, sexual orientation, disability, age, and more
• Reasonable accommodations are available to enable individuals with disabilities to perform essential functions
• Please note: this job description is not exhaustive. Duties and responsibilities may evolve based on business needs

Your Benefits at Exadel  

Exadel benefits vary by location and contract type. Your recruiter will fill you in on the details.

• International projects
• In-office, hybrid, or remote flexibility
• Medical healthcare
• Recognition program
• Ongoing learning & reimbursement 
• Well-being program
• Team events & local benefits 
• Sports compensation 
• Referral bonuses 
• Top-tier equipment provision

Exadel Culture

We lead with trust, respect, and purpose. We believe in open dialogue, creative freedom, and mentorship that helps you grow, lead, and make a real difference. Ours is a culture where ideas are challenged, voices are heard, and your impact matters.

At Superbet, data isn’t a support function, it’s at the heart of every major decision we make. As a Data Scientist, you’ll operate at the intersection of product, commercial, and marketing strategy. Your analyses won’t sit in slide decks; they’ll directly shape how millions of customers engage with our products.

This is a role for very special kind of analyst: who love hard problems, thrive in ambiguity, and get energized by moving from messy data to clear insights that drive strategy. You’ll be expected to not just report what happened, but uncovering why, anticipating what’s next, and influencing what we should do about it.

What You’ll Do

• Be the Decision Engine: Run deep-dive analyses into customer behavior, product usage, and commercial performance. Go beyond surface-level metrics to uncover the drivers behind the phenomenon.
• Shape Strategy with Data: Influence product roadmaps, commercial tactics, and marketing strategies by framing the right questions, running experiments (A/B testing, causal inference etc.), and delivering insights that change the course of decisions.
• Automate Intelligence: Build scalable dashboards, reporting systems, and data tools that enable teams across Superbet to make smarter, faster, data-driven decisions.
• Partner Across the Business: Collaborate with Product Managers, Commercial leaders, Engineers, Designers, and Marketers. You won’t just answer questions, you’ll help define them, challenge assumptions, and bring analytical rigor to high-stakes discussions.
• Tackle Ambiguity: Superbet moves fast. The questions won’t always be clear. You’ll be the one who can bring structure to chaos, translating broad business challenges into sharp, analytical problems.

What We’re Looking For

• Technical Mastery: SQL fluency (we use Snowflake) is a non-negotiable (but, we are open if you can make data talk through other languages!). You should be equally comfortable working with complex data as you are doing deep inquiry through statistical/ML methods and bringing them to life in dashboards (we use Tableau).
• Data Storytelling: You excel at transforming complex analyses into clear, compelling narratives. You can communicate insights effectively to both technical and non-technical stakeholders, making data accessible and actionable for decision-making.
• Commercial & Product Acumen: You don’t just crunch numbers; you understand how data connects to business outcomes, product design, and customer behavior.
• Bias for Impact: You care less about perfect models and more about driving measurable change. Your analyses are only successful if they move the needle.
• Proven Track Record: Previous experience in analytics and product data science roles (ideally in product or commercial domains) where you’ve directly influenced strategy and growth.
• Education: Degree in Data Science, Statistics, Economics, Computer Science/Engg., Mathematics, or a related quantitative field OR equivalent work experience.
• Years of Experience: We are hiring for roles with at least 2+ years of relevant experience.

At Super Technologies, data isn’t a support function, it’s at the heart of every major decision we make. As a Data Scientist, you’ll operate at the intersection of product, commercial, and marketing strategy. Your analyses won’t sit in slide decks; they’ll directly shape how millions of customers engage with our products.

This is a role for very special kind of analyst: who love hard problems, thrive in ambiguity, and get energized by moving from messy data to clear insights that drive strategy. You’ll be expected to not just report what happened, but uncovering why, anticipating what’s next, and influencing what we should do about it.

What You’ll Do

• Be the Decision Engine: Run deep-dive analyses into customer behavior, product usage, and commercial performance. Go beyond surface-level metrics to uncover the drivers behind the phenomenon.
• Shape Strategy with Data: Influence product roadmaps, commercial tactics, and marketing strategies by framing the right questions, running experiments (A/B testing, causal inference etc.), and delivering insights that change the course of decisions.
• Automate Intelligence: Build scalable dashboards, reporting systems, and data tools that enable teams across Super Technologies to make smarter, faster, data-driven decisions.
• Partner Across the Business: Collaborate with Product Managers, Commercial leaders, Engineers, Designers. You won’t just answer questions, you’ll help define them, challenge assumptions, and bring analytical rigor to high-stakes discussions.
• Tackle Ambiguity: Super Technologies moves fast. The questions won’t always be clear. You’ll be the one who can bring structure to chaos, translating broad business challenges into sharp, analytical problems.

What We’re Looking For

• Technical Mastery: SQL fluency (we use Snowflake) is a non-negotiable (but, we are open if you can make data talk through other languages!). You should be equally comfortable working with complex data as you are doing deep inquiry through statistical and ML methods and bringing them to life in dashboards (we use Tableau). It would be also great if you have experience/basic knowledge of python or R.
• Data Storytelling: You excel at transforming complex analyses into clear, compelling narratives. You can communicate insights effectively to both technical and non-technical stakeholders, making data accessible and actionable for decision-making.
• Commercial & Product Acumen: You don’t just crunch numbers; you understand how data connects to business outcomes, product design, and customer behavior.
• Bias for Impact: You care less about perfect models and more about driving measurable change. Your analyses are only successful if they move the needle.
• Proven Track Record: Previous experience in analytics and/or product data science roles (ideally in product or commercial domains) where you’ve directly influenced strategy and growth.
• Education: Degree in Data Science, Statistics, Economics, Computer Science/Engineering, Mathematics, or a related quantitative field OR equivalent work experience.
• Years of Experience: We are hiring for roles with at least 4+ years of relevant experience.

Overview

As a Staff Data Product Manager for the Analytics Platform, you will own the vision and roadmap for our core data foundation, primarily powered by Snowflake. Your mission is to bridge the "Perception vs. Reality" gap: while our platform is technically robust (with minimal incidents in 2025), users often find data hard to use or unclear.
You will define the "what" and "why" of our platform , ensuring it transitions from a reactive service to a strategic partner that empowers every team at Super to leverage data and AI capabilities at scale.

Key responsibilities

Product strategy & vision

• Own and articulate the product strategy and long-term vision for the Analytics Platform by defining the end-to-end analytical product lifecycle —- from data producer contract management and quality guardrails to downstream data consumers, their access patterns, and measurable value realisation.
• Develop a long-term vision for the Analytics Platform, aligning with broader data-driven objectives.
• Stay ahead of industry trends in cloud warehousing, data modeling, and emerging AI technologies.
• Propose and explore new ways of utilizing Snowflake to leverage AI capabilities and drive business value.

User research & advocacy

• Define and continuously evolve a clear measurement framework for Analytics Platform usability and adoption; use it to enable data-driven decisions with platform leaders and to directly shape roadmap priorities based on measurable impact.
• Deeply investigate actual customer needs, workflows, and pain points to eliminate "blind spots" in platform adoption.
• Address the gap between technical uptime and user perception by ensuring data is intuitive, clear, and reliable.
• Champion a user-centric culture, transforming how technical and business teams interact with our data models.

Roadmap & stakeholder management

• Build and maintain a prioritized product roadmap, balancing operational excellence with strategic initiatives.
• Collaborate with Product, Marketing, and Data Science to ensure Analytics platform is focused on most impactful initiatives across all areas

Strategic integration

• Partner with Product teams to ensure the Analytics Platform is a first-class citizen in the development lifecycle, not an afterthought.
• Partner with the Analytics Platform and Data leadership to transform high-level objectives into vision, direction and roadmap for a scalable, reliable technical platform.

Execution & delivery

• Translate business goals into well-defined problem statements, user stories, and acceptance criteria.
• Manage the development cycle in an Agile environment, providing clarity on priorities and monitoring progress.
• Ensure every initiative has a defined "Problem to Solve" and clear success measurement.

Qualifications

1. Education & experience

• Bachelor’s or Master’s degree in Business, Computer Science, Data Science, or a related field.
• 6–8+ years of product management experience, specifically with data products or analytics platforms.

2. Technical & domain expertise

• Strong familiarity with Analytics databases (e.g Snowflake, BigQuery, Redshift), ETL pipelines, DWH concepts and BI tools.
• Ability to convert complex technical concepts into clear business value.
• Proven track record in leading cross-functional teams

3. Strong differentiators

• Previous experience driving large-scale data product initiatives from ideation to launch
• Experience in entertainment, online gaming, or sports betting industries.

Overview

As a Staff Data Product Manager for the Analytics Platform, you will own the vision and roadmap for our core data foundation, primarily powered by Snowflake. Your mission is to bridge the "Perception vs. Reality" gap: while our platform is technically robust (with minimal incidents in 2025), users often find data hard to use or unclear.
You will define the "what" and "why" of our platform , ensuring it transitions from a reactive service to a strategic partner that empowers every team at Super to leverage data and AI capabilities at scale.

Key responsibilities

Product strategy & vision

• Own and articulate the product strategy and long-term vision for the Analytics Platform by defining the end-to-end analytical product lifecycle —- from data producer contract management and quality guardrails to downstream data consumers, their access patterns, and measurable value realisation.
• Develop a long-term vision for the Analytics Platform, aligning with broader data-driven objectives.
• Stay ahead of industry trends in cloud warehousing, data modeling, and emerging AI technologies.
• Propose and explore new ways of utilizing Snowflake to leverage AI capabilities and drive business value.

User research & advocacy

• Define and continuously evolve a clear measurement framework for Analytics Platform usability and adoption; use it to enable data-driven decisions with platform leaders and to directly shape roadmap priorities based on measurable impact.
• Deeply investigate actual customer needs, workflows, and pain points to eliminate "blind spots" in platform adoption.
• Address the gap between technical uptime and user perception by ensuring data is intuitive, clear, and reliable.
• Champion a user-centric culture, transforming how technical and business teams interact with our data models.

Roadmap & stakeholder management

• Build and maintain a prioritized product roadmap, balancing operational excellence with strategic initiatives.
• Collaborate with Product, Marketing, and Data Science to ensure Analytics platform is focused on most impactful initiatives across all areas

Strategic integration

• Partner with Product teams to ensure the Analytics Platform is a first-class citizen in the development lifecycle, not an afterthought.
• Partner with the Analytics Platform and Data leadership to transform high-level objectives into vision, direction and roadmap for a scalable, reliable technical platform.

Execution & delivery

• Translate business goals into well-defined problem statements, user stories, and acceptance criteria.
• Manage the development cycle in an Agile environment, providing clarity on priorities and monitoring progress.
• Ensure every initiative has a defined "Problem to Solve" and clear success measurement.

Qualifications

1. Education & experience

• Bachelor’s or Master’s degree in Business, Computer Science, Data Science, or a related field.
• 6–8+ years of product management experience, specifically with data products or analytics platforms.

2. Technical & domain expertise

• Strong familiarity with Analytics databases (e.g Snowflake, BigQuery, Redshift), ETL pipelines, DWH concepts and BI tools.
• Ability to convert complex technical concepts into clear business value.
• Proven track record in leading cross-functional teams

3. Strong differentiators

• Previous experience driving large-scale data product initiatives from ideation to launch
• Experience in entertainment, online gaming, or sports betting industries.

Overview

As a Staff Data Product Manager for the Analytics Platform, you will own the vision and roadmap for our core data foundation, primarily powered by Snowflake. Your mission is to bridge the "Perception vs. Reality" gap: while our platform is technically robust (with minimal incidents in 2025), users often find data hard to use or unclear.
You will define the "what" and "why" of our platform , ensuring it transitions from a reactive service to a strategic partner that empowers every team at Super to leverage data and AI capabilities at scale.

Key responsibilities

Product strategy & vision

• Own and articulate the product strategy and long-term vision for the Analytics Platform by defining the end-to-end analytical product lifecycle —- from data producer contract management and quality guardrails to downstream data consumers, their access patterns, and measurable value realisation.
• Develop a long-term vision for the Analytics Platform, aligning with broader data-driven objectives.
• Stay ahead of industry trends in cloud warehousing, data modeling, and emerging AI technologies.
• Propose and explore new ways of utilizing Snowflake to leverage AI capabilities and drive business value.

User research & advocacy

• Define and continuously evolve a clear measurement framework for Analytics Platform usability and adoption; use it to enable data-driven decisions with platform leaders and to directly shape roadmap priorities based on measurable impact.
• Deeply investigate actual customer needs, workflows, and pain points to eliminate "blind spots" in platform adoption.
• Address the gap between technical uptime and user perception by ensuring data is intuitive, clear, and reliable.
• Champion a user-centric culture, transforming how technical and business teams interact with our data models.

Roadmap & stakeholder management

• Build and maintain a prioritized product roadmap, balancing operational excellence with strategic initiatives.
• Collaborate with Product, Marketing, and Data Science to ensure Analytics platform is focused on most impactful initiatives across all areas

Strategic integration

• Partner with Product teams to ensure the Analytics Platform is a first-class citizen in the development lifecycle, not an afterthought.
• Partner with the Analytics Platform and Data leadership to transform high-level objectives into vision, direction and roadmap for a scalable, reliable technical platform.

Execution & delivery

• Translate business goals into well-defined problem statements, user stories, and acceptance criteria.
• Manage the development cycle in an Agile environment, providing clarity on priorities and monitoring progress.
• Ensure every initiative has a defined "Problem to Solve" and clear success measurement.

Qualifications

1. Education & experience

• Bachelor’s or Master’s degree in Business, Computer Science, Data Science, or a related field.
• 6–8+ years of product management experience, specifically with data products or analytics platforms.

2. Technical & domain expertise

• Strong familiarity with Analytics databases (e.g Snowflake, BigQuery, Redshift), ETL pipelines, DWH concepts and BI tools.
• Ability to convert complex technical concepts into clear business value.
• Proven track record in leading cross-functional teams

3. Strong differentiators

• Previous experience driving large-scale data product initiatives from ideation to launch
• Experience in entertainment, online gaming, or sports betting industries.

Overview

As a Staff Data Product Manager for the Analytics Platform, you will own the vision and roadmap for our core data foundation, primarily powered by Snowflake. Your mission is to bridge the "Perception vs. Reality" gap: while our platform is technically robust (with minimal incidents in 2025), users often find data hard to use or unclear.
You will define the "what" and "why" of our platform , ensuring it transitions from a reactive service to a strategic partner that empowers every team at Super to leverage data and AI capabilities at scale.

Key responsibilities

Product strategy & vision

• Own and articulate the product strategy and long-term vision for the Analytics Platform by defining the end-to-end analytical product lifecycle —- from data producer contract management and quality guardrails to downstream data consumers, their access patterns, and measurable value realisation.
• Develop a long-term vision for the Analytics Platform, aligning with broader data-driven objectives.
• Stay ahead of industry trends in cloud warehousing, data modeling, and emerging AI technologies.
• Propose and explore new ways of utilizing Snowflake to leverage AI capabilities and drive business value.

User research & advocacy

• Define and continuously evolve a clear measurement framework for Analytics Platform usability and adoption; use it to enable data-driven decisions with platform leaders and to directly shape roadmap priorities based on measurable impact.
• Deeply investigate actual customer needs, workflows, and pain points to eliminate "blind spots" in platform adoption.
• Address the gap between technical uptime and user perception by ensuring data is intuitive, clear, and reliable.
• Champion a user-centric culture, transforming how technical and business teams interact with our data models.

Roadmap & stakeholder management

• Build and maintain a prioritized product roadmap, balancing operational excellence with strategic initiatives.
• Collaborate with Product, Marketing, and Data Science to ensure Analytics platform is focused on most impactful initiatives across all areas

Strategic integration

• Partner with Product teams to ensure the Analytics Platform is a first-class citizen in the development lifecycle, not an afterthought.
• Partner with the Analytics Platform and Data leadership to transform high-level objectives into vision, direction and roadmap for a scalable, reliable technical platform.

Execution & delivery

• Translate business goals into well-defined problem statements, user stories, and acceptance criteria.
• Manage the development cycle in an Agile environment, providing clarity on priorities and monitoring progress.
• Ensure every initiative has a defined "Problem to Solve" and clear success measurement.

Qualifications

1. Education & experience

• Bachelor’s or Master’s degree in Business, Computer Science, Data Science, or a related field.
• 6–8+ years of product management experience, specifically with data products or analytics platforms.

2. Technical & domain expertise

• Strong familiarity with Analytics databases (e.g Snowflake, BigQuery, Redshift), ETL pipelines, DWH concepts and BI tools.
• Ability to convert complex technical concepts into clear business value.
• Proven track record in leading cross-functional teams

3. Strong differentiators

• Previous experience driving large-scale data product initiatives from ideation to launch
• Experience in entertainment, online gaming, or sports betting industries.

Are you excited about building analytics foundations that people can truly rely on, turning complex business questions into trusted datasets, metrics, and reporting experiences? At Super Technologies, data is a strategic enabler of decision-making, experimentation, and performance measurement. Our Analytics Platform team builds the foundations that make data reliable, accessible, and actionable, partnering with product, commercial, and engineering teams to measure what matters.

You’ll be joining a mature and growing community of 40+ data engineers and analytics engineers who are shaping one of the most advanced data ecosystems in the industry.

What you'll be doing:

• Design and build curated analytical datasets, metric implementation, and semantic models that enable consistent self-service analytics across the company
• Work hands-on with data warehouse modelling to turn evolving product and business needs into scalable, reusable data structures
• Partner closely with product, data scientists and business stakeholders to clarify requirements and translate them into reliable data models and reporting-ready outputs
• Build and own production dashboards (Tableau) on top of curated datasets and metric definitions, ensuring correctness, performance, and a consistent “single source of truth”
• Contribute to data quality, observability, lineage, and documentation practices to increase trust and reduce firefighting
• Promote reuse over reinvention, identify ad-hoc logic in reporting views or custom SQL and refactor it into curated, high-quality models that multiple teams can rely on.
• Raise the engineering bar through reviews, testing, automation, and pragmatic architectural improvements
• Apply engineering rigor to analytics - treat semantics as code utilizing version control, testing, automation, and CI/CD practices to manage the lifecycle of our business logic.
• Drive self-service adoption - create the foundations that allow analysts and business users to explore data safely and independently, without needing to reinvent the wheel.
• Work embedded within Data Engineering squads, collaborating daily with both data engineers and analysts on shared foundations and end-to-end delivery

We're looking for:

• Strong SQL skills and proven experience building analytical datasets and metrics in a modern data warehouse (Snowflake preferred, BigQuery, Redshift and similar also valuable)
• Solid understanding of data warehouse modeling and best practices (dimensional modeling, fact/dimension design, grains, slowly changing dimensions, semantic consistency)
• Experience working with reporting and BI tools (Tableau preferred), including understanding how data sources, extracts, and dashboard logic impact correctness, performance, and trust
• A production mindset: you care about reliability, maintainability, documentation, and operational ownership, not just creating a dataset once
• Strong ownership and collaboration skills, able to drive clarity in ambiguous problem spaces and partner effectively with both technical and non-technical teams
• Excellent communication skills with a pragmatic, problem-solving approach

Bonus points for:

• Experience with orchestration and workflow tooling (Airflow or similar)
• Experience with data cataloging, lineage, and governance tooling (e.g., DataHub)
• Background in product-led, experimentation-driven, or high-growth environments where definitions evolve quickly
• Experience supporting downstream operational consumers (e.g., CRM/audience platforms) or ML/feature engineering use cases
• Familiarity with streaming/event-heavy ecosystems (Kafka or similar)

Are you excited about building analytics foundations that people can truly rely on, turning complex business questions into trusted datasets, metrics, and reporting experiences? At Super Technologies, data is a strategic enabler of decision-making, experimentation, and performance measurement. Our Analytics Platform team builds the foundations that make data reliable, accessible, and actionable, partnering with product, commercial, and engineering teams to measure what matters.

You’ll be joining a mature and growing community of 40+ data engineers and analytics engineers who are shaping one of the most advanced data ecosystems in the industry.

What you'll be doing:

• Design and build curated analytical datasets, metric implementation, and semantic models that enable consistent self-service analytics across the company
• Work hands-on with data warehouse modelling to turn evolving product and business needs into scalable, reusable data structures
• Partner closely with product, data scientists and business stakeholders to clarify requirements and translate them into reliable data models and reporting-ready outputs
• Build and own production dashboards (Tableau) on top of curated datasets and metric definitions, ensuring correctness, performance, and a consistent “single source of truth”
• Contribute to data quality, observability, lineage, and documentation practices to increase trust and reduce firefighting
• Promote reuse over reinvention, identify ad-hoc logic in reporting views or custom SQL and refactor it into curated, high-quality models that multiple teams can rely on.
• Raise the engineering bar through reviews, testing, automation, and pragmatic architectural improvements
• Apply engineering rigor to analytics - treat semantics as code utilizing version control, testing, automation, and CI/CD practices to manage the lifecycle of our business logic.
• Drive self-service adoption - create the foundations that allow analysts and business users to explore data safely and independently, without needing to reinvent the wheel.
• Work embedded within Data Engineering squads, collaborating daily with both data engineers and analysts on shared foundations and end-to-end delivery

We're looking for:

• Strong SQL skills and proven experience building analytical datasets and metrics in a modern data warehouse (Snowflake preferred, BigQuery, Redshift and similar also valuable)
• Solid understanding of data warehouse modeling and best practices (dimensional modeling, fact/dimension design, grains, slowly changing dimensions, semantic consistency)
• Experience working with reporting and BI tools (Tableau preferred), including understanding how data sources, extracts, and dashboard logic impact correctness, performance, and trust
• A production mindset: you care about reliability, maintainability, documentation, and operational ownership, not just creating a dataset once
• Strong ownership and collaboration skills, able to drive clarity in ambiguous problem spaces and partner effectively with both technical and non-technical teams
• Excellent communication skills with a pragmatic, problem-solving approach

Bonus points for:

• Experience with orchestration and workflow tooling (Airflow or similar)
• Experience with data cataloging, lineage, and governance tooling (e.g., DataHub)
• Background in product-led, experimentation-driven, or high-growth environments where definitions evolve quickly
• Experience supporting downstream operational consumers (e.g., CRM/audience platforms) or ML/feature engineering use cases
• Familiarity with streaming/event-heavy ecosystems (Kafka or similar)

The Role

At Super technologies, data isn’t a support function, it’s at the heart of every major decision we make. As a Senior Scientist, you’ll operate at the intersection of product, commercial, and marketing strategy. Your analyses won’t sit in slide decks; they’ll directly shape how millions of customers engage with our products.

This is a role for very special kind of analyst: who love hard problems, thrive in ambiguity, and get energized by moving from messy data to clear insights that drive strategy. You’ll be expected to not just report what happened, but uncovering why, anticipating what’s next, and influencing what we should do about it.

What You’ll Do

• Be the Decision Engine: Run deep-dive analyses into customer behaviour, product usage, and commercial performance. Go beyond surface-level metrics to uncover the drivers behind the phenomenon.
• Shape Strategy with Data: Influence product roadmaps, commercial tactics, and marketing strategies by framing the right questions, running experiments (A/B testing, causal inference etc.), and delivering insights that change the course of decisions.
• Automate Intelligence: Build scalable dashboards, reporting systems, and data tools that enable teams across Superbet to make smarter, faster, data-driven decisions.
• Partner Across the Business: Collaborate with Product Managers, Commercial leaders, Engineers, Designers, and Marketers. You won’t just answer questions, you’ll help define them, challenge assumptions, and bring analytical rigor to high-stakes discussions.
• Tackle Ambiguity: Superbet moves fast. The questions won’t always be clear. You’ll be the one who can bring structure to chaos, translating broad business challenges into sharp, analytical problems.

What We’re Looking For

• Technical Mastery: SQL fluency (we use Snowflake) is a non-negotiable (but, we are open if you can make data talk through other languages!). You should be equally comfortable working with complex data as you are doing deep inquiry through statistical/ML methods and bringing them to life in dashboards (we use Tableau).
• Data Storytelling: You excel at transforming complex analyses into clear, compelling narratives. You can communicate insights effectively to both technical and non-technical stakeholders, making data accessible and actionable for decision-making.
• Commercial & Product Acumen: You don’t just crunch numbers; you understand how data connects to business outcomes, product design, and customer behavior.
• Bias for Impact: You care less about perfect models and more about driving measurable change. Your analyses are only successful if they move the needle.
• Proven Track Record: Previous experience in analytics and/or product data science roles (ideally in product or commercial domains) where you’ve directly influenced strategy and growth.
• Education: Degree in Data Science, Statistics, Economics, Computer Science/Engg., Mathematics, or a related quantitative field OR equivalent work experience.
• Years of Experience: We are hiring for roles with at least 2+ years of relevant experience.

Why Join Us?

• High Impact
  • Your datasets will be used daily by teams making product decisions, running experiments, and driving performance.
• Real Scale, Real Problems
  • Handle serious data volumes. We’re talking millions of events per day, multiple sources, and zero fluff.
• Freedom to Shape
  • Influence our data architecture, tooling, and best practices. You're not just implementing—you’re building.
• Solid Benefits
  • Competitive compensation & performance-based bonuses
  • Open vacation policy & hybrid work flexibility
  • Health support, wellness perks & team social budget

The Role

At Super technologies, data isn’t a support function, it’s at the heart of every major decision we make. As a Senior Scientist, you’ll operate at the intersection of product, commercial, and marketing strategy. Your analyses won’t sit in slide decks; they’ll directly shape how millions of customers engage with our products.

This is a role for very special kind of analyst: who love hard problems, thrive in ambiguity, and get energized by moving from messy data to clear insights that drive strategy. You’ll be expected to not just report what happened, but uncovering why, anticipating what’s next, and influencing what we should do about it.

What You’ll Do

• Be the Decision Engine: Run deep-dive analyses into customer behaviour, product usage, and commercial performance. Go beyond surface-level metrics to uncover the drivers behind the phenomenon.
• Shape Strategy with Data: Influence product roadmaps, commercial tactics, and marketing strategies by framing the right questions, running experiments (A/B testing, causal inference etc.), and delivering insights that change the course of decisions.
• Automate Intelligence: Build scalable dashboards, reporting systems, and data tools that enable teams across Superbet to make smarter, faster, data-driven decisions.
• Partner Across the Business: Collaborate with Product Managers, Commercial leaders, Engineers, Designers, and Marketers. You won’t just answer questions, you’ll help define them, challenge assumptions, and bring analytical rigor to high-stakes discussions.
• Tackle Ambiguity: Superbet moves fast. The questions won’t always be clear. You’ll be the one who can bring structure to chaos, translating broad business challenges into sharp, analytical problems.

What We’re Looking For

• Technical Mastery: SQL fluency (we use Snowflake) is a non-negotiable (but, we are open if you can make data talk through other languages!). You should be equally comfortable working with complex data as you are doing deep inquiry through statistical/ML methods and bringing them to life in dashboards (we use Tableau).
• Data Storytelling: You excel at transforming complex analyses into clear, compelling narratives. You can communicate insights effectively to both technical and non-technical stakeholders, making data accessible and actionable for decision-making.
• Commercial & Product Acumen: You don’t just crunch numbers; you understand how data connects to business outcomes, product design, and customer behavior.
• Bias for Impact: You care less about perfect models and more about driving measurable change. Your analyses are only successful if they move the needle.
• Proven Track Record: Previous experience in analytics and/or product data science roles (ideally in product or commercial domains) where you’ve directly influenced strategy and growth.
• Education: Degree in Data Science, Statistics, Economics, Computer Science/Engg., Mathematics, or a related quantitative field OR equivalent work experience.
• Years of Experience: We are hiring for roles with at least 2+ years of relevant experience.

Why Join Us?

• High Impact
  • Your datasets will be used daily by teams making product decisions, running experiments, and driving performance.
• Real Scale, Real Problems
  • Handle serious data volumes. We’re talking millions of events per day, multiple sources, and zero fluff.
• Freedom to Shape
  • Influence our data architecture, tooling, and best practices. You're not just implementing—you’re building.
• Solid Benefits
  • Competitive compensation & performance-based bonuses
  • Open vacation policy & hybrid work flexibility
  • Health support, wellness perks & team social budget

The Role

At Super technologies, data isn’t a support function, it’s at the heart of every major decision we make. As a Senior Scientist, you’ll operate at the intersection of product, commercial, and marketing strategy. Your analyses won’t sit in slide decks; they’ll directly shape how millions of customers engage with our products.

This is a role for very special kind of analyst: who love hard problems, thrive in ambiguity, and get energized by moving from messy data to clear insights that drive strategy. You’ll be expected to not just report what happened, but uncovering why, anticipating what’s next, and influencing what we should do about it.

What You’ll Do

• Be the Decision Engine: Run deep-dive analyses into customer behaviour, product usage, and commercial performance. Go beyond surface-level metrics to uncover the drivers behind the phenomenon.
• Shape Strategy with Data: Influence product roadmaps, commercial tactics, and marketing strategies by framing the right questions, running experiments (A/B testing, causal inference etc.), and delivering insights that change the course of decisions.
• Automate Intelligence: Build scalable dashboards, reporting systems, and data tools that enable teams across Superbet to make smarter, faster, data-driven decisions.
• Partner Across the Business: Collaborate with Product Managers, Commercial leaders, Engineers, Designers, and Marketers. You won’t just answer questions, you’ll help define them, challenge assumptions, and bring analytical rigor to high-stakes discussions.
• Tackle Ambiguity: Superbet moves fast. The questions won’t always be clear. You’ll be the one who can bring structure to chaos, translating broad business challenges into sharp, analytical problems.

What We’re Looking For

• Technical Mastery: SQL fluency (we use Snowflake) is a non-negotiable (but, we are open if you can make data talk through other languages!). You should be equally comfortable working with complex data as you are doing deep inquiry through statistical/ML methods and bringing them to life in dashboards (we use Tableau).
• Data Storytelling: You excel at transforming complex analyses into clear, compelling narratives. You can communicate insights effectively to both technical and non-technical stakeholders, making data accessible and actionable for decision-making.
• Commercial & Product Acumen: You don’t just crunch numbers; you understand how data connects to business outcomes, product design, and customer behavior.
• Bias for Impact: You care less about perfect models and more about driving measurable change. Your analyses are only successful if they move the needle.
• Proven Track Record: Previous experience in analytics and/or product data science roles (ideally in product or commercial domains) where you’ve directly influenced strategy and growth.
• Education: Degree in Data Science, Statistics, Economics, Computer Science/Engg., Mathematics, or a related quantitative field OR equivalent work experience.
• Years of Experience: We are hiring for roles with at least 2+ years of relevant experience.

Why Join Us?

• High Impact
  • Your datasets will be used daily by teams making product decisions, running experiments, and driving performance.
• Real Scale, Real Problems
  • Handle serious data volumes. We’re talking millions of events per day, multiple sources, and zero fluff.
• Freedom to Shape
  • Influence our data architecture, tooling, and best practices. You're not just implementing—you’re building.
• Solid Benefits
  • Competitive compensation & performance-based bonuses
  • Open vacation policy & hybrid work flexibility
  • Health support, wellness perks & team social budget

The Role

At Super technologies, data isn’t a support function, it’s at the heart of every major decision we make. As a Senior Scientist, you’ll operate at the intersection of product, commercial, and marketing strategy. Your analyses won’t sit in slide decks; they’ll directly shape how millions of customers engage with our products.

This is a role for very special kind of analyst: who love hard problems, thrive in ambiguity, and get energized by moving from messy data to clear insights that drive strategy. You’ll be expected to not just report what happened, but uncovering why, anticipating what’s next, and influencing what we should do about it.

What You’ll Do

• Be the Decision Engine: Run deep-dive analyses into customer behaviour, product usage, and commercial performance. Go beyond surface-level metrics to uncover the drivers behind the phenomenon.
• Shape Strategy with Data: Influence product roadmaps, commercial tactics, and marketing strategies by framing the right questions, running experiments (A/B testing, causal inference etc.), and delivering insights that change the course of decisions.
• Automate Intelligence: Build scalable dashboards, reporting systems, and data tools that enable teams across Superbet to make smarter, faster, data-driven decisions.
• Partner Across the Business: Collaborate with Product Managers, Commercial leaders, Engineers, Designers, and Marketers. You won’t just answer questions, you’ll help define them, challenge assumptions, and bring analytical rigor to high-stakes discussions.
• Tackle Ambiguity: Superbet moves fast. The questions won’t always be clear. You’ll be the one who can bring structure to chaos, translating broad business challenges into sharp, analytical problems.

What We’re Looking For

• Technical Mastery: SQL fluency (we use Snowflake) is a non-negotiable (but, we are open if you can make data talk through other languages!). You should be equally comfortable working with complex data as you are doing deep inquiry through statistical/ML methods and bringing them to life in dashboards (we use Tableau).
• Data Storytelling: You excel at transforming complex analyses into clear, compelling narratives. You can communicate insights effectively to both technical and non-technical stakeholders, making data accessible and actionable for decision-making.
• Commercial & Product Acumen: You don’t just crunch numbers; you understand how data connects to business outcomes, product design, and customer behavior.
• Bias for Impact: You care less about perfect models and more about driving measurable change. Your analyses are only successful if they move the needle.
• Proven Track Record: Previous experience in analytics and/or product data science roles (ideally in product or commercial domains) where you’ve directly influenced strategy and growth.
• Education: Degree in Data Science, Statistics, Economics, Computer Science/Engg., Mathematics, or a related quantitative field OR equivalent work experience.
• Years of Experience: We are hiring for roles with at least 2+ years of relevant experience.

Why Join Us?

• High Impact
  • Your datasets will be used daily by teams making product decisions, running experiments, and driving performance.
• Real Scale, Real Problems
  • Handle serious data volumes. We’re talking millions of events per day, multiple sources, and zero fluff.
• Freedom to Shape
  • Influence our data architecture, tooling, and best practices. You're not just implementing—you’re building.
• Solid Benefits
  • Competitive compensation & performance-based bonuses
  • Open vacation policy & hybrid work flexibility
  • Health support, wellness perks & team social budget

About the job

The world’s most critical--and at risk--business applications have been neglected for far too long. Onapsis eliminates this blind spot by providing cybersecurity solutions dedicated to business-critical applications. Whether running on premises, in the cloud, or in a hybrid environment, Onapsis helps nearly 30% of the Forbes Global 100 understand the threats and risks across their SAP and Oracle landscapes.

We are seeking a Senior Data Engineer to join our mission-driven team. This role is ideal for experienced data engineers with a proven track record in architecting scalable data pipelines, leveraging cloud technologies, and contributing to high-impact cybersecurity solutions. You will be responsible for building high-performance ETL frameworks, optimizing data platforms, and contributing directly to the enhancement of our customers' threat detection, response, and remediation capabilities.

What you will be doing, your legacy: 

You will be working directly with company Principal Engineers evaluating, scoping, proposing, and building features to fulfill business solution requirements to protect our customers. You will play a direct role in laying the technical foundation for a new product offering. Additionally, you will be working with Engineering and DevOps to deliver high-quality products and services while also working closely with security and IT professionals to ensure safe and secure best practices are followed. 

Responsibilities:

• Architect and Design Scalable Data Solutions: Design/develop/maintain Data lakehouse solutions (Iceberg/Delta Lake /Hudi) applying industry best practices and structuring / optimizing the data according to data access patterns.
• Data Pipeline Development: Implement ETL/ELT pipelines using cloud technologies (Spark / pySpark / Glue, Kinesis Streams / Iceberg) to load the data into a Lakehouse for both efficient ML processing and UI reporting.
• Implement data models and data processing frameworks (Spark, Kafka, Snowflake) to ingest, transform, and load large datasets into Data Lakehouse techs (Apache Iceberg, Apache Delta Lake or Apache Hudi), ensuring high availability and reliability of data.
• Advanced Data Integration: Develop solutions that integrate multiple data sources into Snowflake or similar data warehouses to enable real-time analytics and reporting across dashboards.
• AI/ML Integration: Collaborate with cross-functional teams to co-develop AI-driven features identifying patterns and anomalies in client data using AI/ML technologies (python).
• Compliance and Security: Ensure compliance with industry standards and secure best practices (SOX, SOC 1/2), by implementing data governance frameworks, monitoring data pipelines, and optimizing cloud database architectures to protect sensitive information.
• Stakeholder Collaboration: Work closely with stakeholders, including analysts, engineers, and product managers, to understand their data needs, propose solutions, and drive data-driven decision-making by delivering actionable insights.
• Data Infrastructure Monitoring: Continuously monitor, troubleshoot, and enhance data pipelines, leveraging CI/CD tools (Docker, Jenkins, GitHub Actions) and orchestrating workflows using Apache Airflow to maintain operational efficiency.
• Leadership and Mentorship: Provide hands-on mentorship and technical guidance to junior engineers, including code reviews and architecture discussions.
• Documentation and Governance: Establish comprehensive documentation for data architecture, governance, and processes to ensure scalability, compliance, and security.

Qualifications:

• 5+ years of proven experience as a Data Engineer or in a similar role with a deep understanding of data architecture and cloud-based ETL/ELT frameworks.
• Strong experience with AWS (preferably) or Azure , particularly with Glue, EMR, S3, Lambda. Databricks, Snowflake, Synapse experience is a bonus.
• Proficiency in big data technologies such as Apache Spark, Kafka, Hadoop, and Databricks for distributed data processing.
• Proficiency with Python libraries for data processing and ML (e.g., Pandas, NumPy, Polars, Scikit-learn, PyTorch, TensorFlow).
• Hands-on experience in building real-time data processing and AI/ML-driven analytics solutions (SageMaker, Bedrock, NLP, Power BI).
• Ability to architect and manage data lakehouse solutions (Iceberg / Delta Lake / Hudi) or classic warehouse solutions (Redshift, Snowflake).
• Familiarity with compliance and audit requirements (SOX, SOC 1/2, GDPR) and implementing data governance and security frameworks.
• Strong problem-solving skills with a focus on data integrity, scalability, and performance optimization.
• Experience with CI/CD tools (Jenkins, GitHub Actions, Docker) and data orchestration platforms (Apache Airflow).

Preferred Qualifications:

• Experience with advanced data architecture principles (medallion architecture, materialized views, task scheduling).
• Experience using BI tools (e.g., Power BI, Tableau) for real-time analytics and operational reporting

What we offer: 

• A role in shaping the future of protecting the most critical applications that run the world's business and a career that grows as the company grows.
• A unique culture of high achievement and teamwork.
• Supportive and humble colleagues are the space's top problem solvers and innovators.
• Financial security through competitive compensation and incentives.

Location: Onapsis is established a new development center in Bucharest. This is a hybrid role (1-2 days per week from the office), so candidates must be commutable to Bucharest every week.

About Onapsis:

Onapsis protects the business applications that run the global economy. The Onapsis Platform delivers vulnerability management, change assurance, and continuous compliance for business applications from leading vendors such as SAP, Oracle, and others. The Onapsis Platform is powered by the Onapsis Research Labs, the team responsible for the discovery and mitigation of more than 1,000 zero-day vulnerabilities in business applications.

Onapsis is headquartered in Boston, MA, with egional offices in Heidelberg, Germany; Buenos Aires, Argentina; Texas, USA, and now in Bucharest, Romania; and proudly serves hundreds of the world’s leading brands, including close to 30% of the Forbes Global 100, six of the top 10 automotive companies, five of the top 10 chemical companies, four of the top 10 technology companies, and three of the top 10 oil and gas companies. 

For more information, connect with Onapsis on LinkedIn or visit https://www.onapsis.com.

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