Join Exadel as a Senior/Lead Data Developer and bring logic to life. Solve analytical challenges and build solutions that matter - with a sharp, collaborative 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 international consulting firm that helps companies of all sizes have a better impact on the world. Company capabilities focus on supporting the private and public sectors with their people, processes, and digital technology challenges.

What You’ll Do

• Design, build, and maintain scalable data pipelines primarily within Google Cloud Platform
• Develop integration and transformation workflows between cloud data services and on-prem Oracle databases
• Work closely with trading, risk, and analytics teams to understand data requirements and deliver real-time and batch data solutions
• Optimise and monitor performance of data systems to support latency-sensitive trading applications
• Collaborate with cross-functional teams using Agile/Scrum methodologies to deliver business-critical data projects, provide technical assistance to the team 
• Ensure robust data governance, lineage, and compliance (including MiFID II, FCA, and other regulatory standards)
• Automate data workflows using Terraform, CI/CD pipelines, and containerisation tools (Docker/Kubernetes)

What You Bring

• Strong experience with Google Cloud Platform (BigQuery, DataPlex, DBT, Pub/Sub, Dataflow, Redshift)
• Expertise in Oracle SQL, PL/SQL, and working with complex stored procedures and large datasets
• Proficiency in programming languages such as Python, Java, or Scala
• Experience with streaming and messaging systems (e.g. Jenkins, GitLab), and container orchestration (Kubernetes)
• Experience working with Infrastructure as Code, preferably Terraform, to manage cloud data infrastructure.
• Deep understanding of data modelling, data warehousing, and ETL/ELT design patterns
• Demonstrated team leadership experience
• Familiarity with Agile development practices (Scrum, Kanban, Jira)
• Exposure to financial markets, trading systems, or related high-performance environments is a strong plus

Nice to have

• GCP certification (e.g., Professional Data Engineer or similar) will be considered a strong advantage
• Experience with Amazon Web Services (AWS)
• Knowledge of regulatory reporting, market data, or trade surveillance systems
• Experience with Apache Airflow or similar orchestration tools
• Understanding of data security practices and compliance frameworks

English level

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/Lead Data Developer and bring logic to life. Solve analytical challenges and build solutions that matter - with a sharp, collaborative 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 international consulting firm that helps companies of all sizes have a better impact on the world. Company capabilities focus on supporting the private and public sectors with their people, processes, and digital technology challenges.

What You’ll Do

• Design, build, and maintain scalable data pipelines primarily within Google Cloud Platform
• Develop integration and transformation workflows between cloud data services and on-prem Oracle databases
• Work closely with trading, risk, and analytics teams to understand data requirements and deliver real-time and batch data solutions
• Optimise and monitor performance of data systems to support latency-sensitive trading applications
• Collaborate with cross-functional teams using Agile/Scrum methodologies to deliver business-critical data projects, provide technical assistance to the team 
• Ensure robust data governance, lineage, and compliance (including MiFID II, FCA, and other regulatory standards)
• Automate data workflows using Terraform, CI/CD pipelines, and containerisation tools (Docker/Kubernetes)

What You Bring

• Strong experience with Google Cloud Platform (BigQuery, DataPlex, DBT, Pub/Sub, Dataflow, Redshift)
• Expertise in Oracle SQL, PL/SQL, and working with complex stored procedures and large datasets
• Proficiency in programming languages such as Python, Java, or Scala
• Experience with streaming and messaging systems (e.g. Jenkins, GitLab), and container orchestration (Kubernetes)
• Experience working with Infrastructure as Code, preferably Terraform, to manage cloud data infrastructure.
• Deep understanding of data modelling, data warehousing, and ETL/ELT design patterns
• Demonstrated team leadership experience
• Familiarity with Agile development practices (Scrum, Kanban, Jira)
• Exposure to financial markets, trading systems, or related high-performance environments is a strong plus

Nice to have

• GCP certification (e.g., Professional Data Engineer or similar) will be considered a strong advantage
• Experience with Amazon Web Services (AWS)
• Knowledge of regulatory reporting, market data, or trade surveillance systems
• Experience with Apache Airflow or similar orchestration tools
• Understanding of data security practices and compliance frameworks

English level

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/Lead Data Developer and bring logic to life. Solve analytical challenges and build solutions that matter - with a sharp, collaborative 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 international consulting firm that helps companies of all sizes have a better impact on the world. Company capabilities focus on supporting the private and public sectors with their people, processes, and digital technology challenges.

What You’ll Do

• Design, build, and maintain scalable data pipelines primarily within Google Cloud Platform
• Develop integration and transformation workflows between cloud data services and on-prem Oracle databases
• Work closely with trading, risk, and analytics teams to understand data requirements and deliver real-time and batch data solutions
• Optimise and monitor performance of data systems to support latency-sensitive trading applications
• Collaborate with cross-functional teams using Agile/Scrum methodologies to deliver business-critical data projects, provide technical assistance to the team 
• Ensure robust data governance, lineage, and compliance (including MiFID II, FCA, and other regulatory standards)
• Automate data workflows using Terraform, CI/CD pipelines, and containerisation tools (Docker/Kubernetes)

What You Bring

• Strong experience with Google Cloud Platform (BigQuery, DataPlex, DBT, Pub/Sub, Dataflow, Redshift)
• Expertise in Oracle SQL, PL/SQL, and working with complex stored procedures and large datasets
• Proficiency in programming languages such as Python, Java, or Scala
• Experience with streaming and messaging systems (e.g. Jenkins, GitLab), and container orchestration (Kubernetes)
• Experience working with Infrastructure as Code, preferably Terraform, to manage cloud data infrastructure.
• Deep understanding of data modelling, data warehousing, and ETL/ELT design patterns
• Demonstrated team leadership experience
• Familiarity with Agile development practices (Scrum, Kanban, Jira)
• Exposure to financial markets, trading systems, or related high-performance environments is a strong plus

Nice to have

• GCP certification (e.g., Professional Data Engineer or similar) will be considered a strong advantage
• Experience with Amazon Web Services (AWS)
• Knowledge of regulatory reporting, market data, or trade surveillance systems
• Experience with Apache Airflow or similar orchestration tools
• Understanding of data security practices and compliance frameworks

English level

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/Lead Data Developer and bring logic to life. Solve analytical challenges and build solutions that matter - with a sharp, collaborative 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 international consulting firm that helps companies of all sizes have a better impact on the world. Company capabilities focus on supporting the private and public sectors with their people, processes, and digital technology challenges.

What You’ll Do

• Design, build, and maintain scalable data pipelines primarily within Google Cloud Platform
• Develop integration and transformation workflows between cloud data services and on-prem Oracle databases
• Work closely with trading, risk, and analytics teams to understand data requirements and deliver real-time and batch data solutions
• Optimise and monitor performance of data systems to support latency-sensitive trading applications
• Collaborate with cross-functional teams using Agile/Scrum methodologies to deliver business-critical data projects, provide technical assistance to the team 
• Ensure robust data governance, lineage, and compliance (including MiFID II, FCA, and other regulatory standards)
• Automate data workflows using Terraform, CI/CD pipelines, and containerisation tools (Docker/Kubernetes)

What You Bring

• Strong experience with Google Cloud Platform (BigQuery, DataPlex, DBT, Pub/Sub, Dataflow, Redshift)
• Expertise in Oracle SQL, PL/SQL, and working with complex stored procedures and large datasets
• Proficiency in programming languages such as Python, Java, or Scala
• Experience with streaming and messaging systems (e.g. Jenkins, GitLab), and container orchestration (Kubernetes)
• Experience working with Infrastructure as Code, preferably Terraform, to manage cloud data infrastructure.
• Deep understanding of data modelling, data warehousing, and ETL/ELT design patterns
• Demonstrated team leadership experience
• Familiarity with Agile development practices (Scrum, Kanban, Jira)
• Exposure to financial markets, trading systems, or related high-performance environments is a strong plus

Nice to have

• GCP certification (e.g., Professional Data Engineer or similar) will be considered a strong advantage
• Experience with Amazon Web Services (AWS)
• Knowledge of regulatory reporting, market data, or trade surveillance systems
• Experience with Apache Airflow or similar orchestration tools
• Understanding of data security practices and compliance frameworks

English level

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.

As a Staff Machine Learning Engineer in our Applied ML & Research team, you'll drive the development of cutting-edge machine learning solutions that power critical features across our online gaming platforms. Your work will directly impact platform security, user experience, and large-scale data-driven decision-making for hundreds of thousands of users daily.

This role blends hands-on technical work with strategic thinking. You’ll lead by example, contribute high-quality code, and help shape the ML roadmap in the organization through cross-functional collaboration.

What you’ll you be doing:

• Identify high-impact ML opportunities and influence stakeholders to prioritize and support these initiatives.
• Design and develop scalable machine learning models — including classifiers, regressors, and rule-based systems — to solve real-world problems.
• Own the full ML lifecycle: from data exploration and feature engineering to model training, evaluation, and deployment.
• Translate complex technical concepts into clear insights for both technical and non-technical stakeholders.
• Set and guide technical direction across ML projects, ensuring technical best practices as well as alignment with business goals.
• Mentor junior engineers and foster a culture of knowledge sharing and continuous improvement.

We're looking for someone with:

• Master’s degree (or equivalent) in Machine Learning, Data Science, Statistics, Mathematics, Computer Science, or a related field.
• 7+ years of industry experience building and deploying ML models at scale.
• Proven ability to lead cross-functional technical initiatives and influence engineering strategy.
• Proficiency in Python (with libraries like PyTorch, XGBoost, Scikit-learn) and SQL.
• Strong experience with machine learning pipelines and orchestration tools such as Airflow, SageMaker Pipelines, or similar.
• Deep understanding of machine learning fundamentals, including experience with Large Language Models (LLMs) and other emerging ML technologies.
• A track record of shipping production-level ML products and maintaining high code quality.
• Excellent problem-solving skills and ability to scope and disambiguate complex ML projects into clear, achievable milestones.

Bonus points for:

• Familiarity with ML tooling such as MLflow, ZenML, or Metaflow.
• Hands-on experience with AWS services (e.g., EC2, EKS, CloudFormation, Cognito).
• Exposure to streaming data platforms like Kafka.
• Contributions to open-source ML projects or publications in ML conferences.

As a Staff Machine Learning Engineer in our Applied ML & Research team, you'll drive the development of cutting-edge machine learning solutions that power critical features across our online gaming platforms. Your work will directly impact platform security, user experience, and large-scale data-driven decision-making for hundreds of thousands of users daily.

This role blends hands-on technical work with strategic thinking. You’ll lead by example, contribute high-quality code, and help shape the ML roadmap in the organization through cross-functional collaboration.

What you’ll you be doing:

• Identify high-impact ML opportunities and influence stakeholders to prioritize and support these initiatives.
• Design and develop scalable machine learning models — including classifiers, regressors, and rule-based systems — to solve real-world problems.
• Own the full ML lifecycle: from data exploration and feature engineering to model training, evaluation, and deployment.
• Translate complex technical concepts into clear insights for both technical and non-technical stakeholders.
• Set and guide technical direction across ML projects, ensuring technical best practices as well as alignment with business goals.
• Mentor junior engineers and foster a culture of knowledge sharing and continuous improvement.

We're looking for someone with:

• Master’s degree (or equivalent) in Machine Learning, Data Science, Statistics, Mathematics, Computer Science, or a related field.
• 7+ years of industry experience building and deploying ML models at scale.
• Proven ability to lead cross-functional technical initiatives and influence engineering strategy.
• Proficiency in Python (with libraries like PyTorch, XGBoost, Scikit-learn) and SQL.
• Strong experience with machine learning pipelines and orchestration tools such as Airflow, SageMaker Pipelines, or similar.
• Deep understanding of machine learning fundamentals, including experience with Large Language Models (LLMs) and other emerging ML technologies.
• A track record of shipping production-level ML products and maintaining high code quality.
• Excellent problem-solving skills and ability to scope and disambiguate complex ML projects into clear, achievable milestones.

Bonus points for:

• Familiarity with ML tooling such as MLflow, ZenML, or Metaflow.
• Hands-on experience with AWS services (e.g., EC2, EKS, CloudFormation, Cognito).
• Exposure to streaming data platforms like Kafka.
• Contributions to open-source ML projects or publications in ML conferences.

As a Staff Machine Learning Engineer in our Applied ML & Research team, you'll drive the development of cutting-edge machine learning solutions that power critical features across our online gaming platforms. Your work will directly impact platform security, user experience, and large-scale data-driven decision-making for hundreds of thousands of users daily.

This role blends hands-on technical work with strategic thinking. You’ll lead by example, contribute high-quality code, and help shape the ML roadmap in the organization through cross-functional collaboration.

What you’ll you be doing:

• Identify high-impact ML opportunities and influence stakeholders to prioritize and support these initiatives.
• Design and develop scalable machine learning models — including classifiers, regressors, and rule-based systems — to solve real-world problems.
• Own the full ML lifecycle: from data exploration and feature engineering to model training, evaluation, and deployment.
• Translate complex technical concepts into clear insights for both technical and non-technical stakeholders.
• Set and guide technical direction across ML projects, ensuring technical best practices as well as alignment with business goals.
• Mentor junior engineers and foster a culture of knowledge sharing and continuous improvement.

We're looking for someone with:

• Master’s degree (or equivalent) in Machine Learning, Data Science, Statistics, Mathematics, Computer Science, or a related field.
• 7+ years of industry experience building and deploying ML models at scale.
• Proven ability to lead cross-functional technical initiatives and influence engineering strategy.
• Proficiency in Python (with libraries like PyTorch, XGBoost, Scikit-learn) and SQL.
• Strong experience with machine learning pipelines and orchestration tools such as Airflow, SageMaker Pipelines, or similar.
• Deep understanding of machine learning fundamentals, including experience with Large Language Models (LLMs) and other emerging ML technologies.
• A track record of shipping production-level ML products and maintaining high code quality.
• Excellent problem-solving skills and ability to scope and disambiguate complex ML projects into clear, achievable milestones.

Bonus points for:

• Familiarity with ML tooling such as MLflow, ZenML, or Metaflow.
• Hands-on experience with AWS services (e.g., EC2, EKS, CloudFormation, Cognito).
• Exposure to streaming data platforms like Kafka.
• Contributions to open-source ML projects or publications in ML conferences.

As a Staff Machine Learning Engineer in our Applied ML & Research team, you'll drive the development of cutting-edge machine learning solutions that power critical features across our online gaming platforms. Your work will directly impact platform security, user experience, and large-scale data-driven decision-making for hundreds of thousands of users daily.

This role blends hands-on technical work with strategic thinking. You’ll lead by example, contribute high-quality code, and help shape the ML roadmap in the organization through cross-functional collaboration.

What you’ll you be doing:

• Identify high-impact ML opportunities and influence stakeholders to prioritize and support these initiatives.
• Design and develop scalable machine learning models — including classifiers, regressors, and rule-based systems — to solve real-world problems.
• Own the full ML lifecycle: from data exploration and feature engineering to model training, evaluation, and deployment.
• Translate complex technical concepts into clear insights for both technical and non-technical stakeholders.
• Set and guide technical direction across ML projects, ensuring technical best practices as well as alignment with business goals.
• Mentor junior engineers and foster a culture of knowledge sharing and continuous improvement.

We're looking for someone with:

• Master’s degree (or equivalent) in Machine Learning, Data Science, Statistics, Mathematics, Computer Science, or a related field.
• 7+ years of industry experience building and deploying ML models at scale.
• Proven ability to lead cross-functional technical initiatives and influence engineering strategy.
• Proficiency in Python (with libraries like PyTorch, XGBoost, Scikit-learn) and SQL.
• Strong experience with machine learning pipelines and orchestration tools such as Airflow, SageMaker Pipelines, or similar.
• Deep understanding of machine learning fundamentals, including experience with Large Language Models (LLMs) and other emerging ML technologies.
• A track record of shipping production-level ML products and maintaining high code quality.
• Excellent problem-solving skills and ability to scope and disambiguate complex ML projects into clear, achievable milestones.

Bonus points for:

• Familiarity with ML tooling such as MLflow, ZenML, or Metaflow.
• Hands-on experience with AWS services (e.g., EC2, EKS, CloudFormation, Cognito).
• Exposure to streaming data platforms like Kafka.
• Contributions to open-source ML projects or publications in ML conferences.

As a Staff Machine Learning Engineer in our Applied ML & Research team, you'll drive the development of cutting-edge machine learning solutions that power critical features across our online gaming platforms. Your work will directly impact platform security, user experience, and large-scale data-driven decision-making for hundreds of thousands of users daily.

This role blends hands-on technical work with strategic thinking. You’ll lead by example, contribute high-quality code, and help shape the ML roadmap in the organization through cross-functional collaboration.

What you’ll you be doing:

• Identify high-impact ML opportunities and influence stakeholders to prioritize and support these initiatives.
• Design and develop scalable machine learning models — including classifiers, regressors, and rule-based systems — to solve real-world problems.
• Own the full ML lifecycle: from data exploration and feature engineering to model training, evaluation, and deployment.
• Translate complex technical concepts into clear insights for both technical and non-technical stakeholders.
• Set and guide technical direction across ML projects, ensuring technical best practices as well as alignment with business goals.
• Mentor junior engineers and foster a culture of knowledge sharing and continuous improvement.

We're looking for someone with:

• Master’s degree (or equivalent) in Machine Learning, Data Science, Statistics, Mathematics, Computer Science, or a related field.
• 7+ years of industry experience building and deploying ML models at scale.
• Proven ability to lead cross-functional technical initiatives and influence engineering strategy.
• Proficiency in Python (with libraries like PyTorch, XGBoost, Scikit-learn) and SQL.
• Strong experience with machine learning pipelines and orchestration tools such as Airflow, SageMaker Pipelines, or similar.
• Deep understanding of machine learning fundamentals, including experience with Large Language Models (LLMs) and other emerging ML technologies.
• A track record of shipping production-level ML products and maintaining high code quality.
• Excellent problem-solving skills and ability to scope and disambiguate complex ML projects into clear, achievable milestones.

Bonus points for:

• Familiarity with ML tooling such as MLflow, ZenML, or Metaflow.
• Hands-on experience with AWS services (e.g., EC2, EKS, CloudFormation, Cognito).
• Exposure to streaming data platforms like Kafka.
• Contributions to open-source ML projects or publications in ML conferences.

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)

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.

#LI-AC1

#LI-Hybrid

We are looking for a Senior ML Platform Engineer to join our ML Platform team to build, evolve and scale AI Infrastructure that powers Bolt's intelligent services

With over 200 million customers in 50+ countries, Bolt is one of the fastest-growing tech companies in Europe and Africa. And it's all thanks to our people.

We believe in creating an inclusive environment where everyone is welcome, regardless of race, colour, religion, gender identity, sexual orientation, age, or disability.

Our ultimate goal is to make cities for people, not cars, and we need your help to achieve this mission!

The ML Platform Team makes ML/AI easy at scale. We streamline development, testing and deployment of ML/AI systems for hundreds of real-time algorithms. 

We own training orchestration, an inference software stack and infrastructure, and a Feature Store, including VectorSearch and RAG tooling. We develop LLM tools and CI/CD for ML, covering the whole range of ML infrastructure needs.

Our tech stack includes TypeScript, Python, Spark (batch and structured streaming), Airflow, n8n, MLflow, LiteLLM, AWS SageMaker, Redis, Elasticsearch, Docker, Kubernetes, AWS (S3, EKS), Terraform, Great Expectations. 

• Designing, building, and optimising components of Bolt’s ML Platform.
• Optimise and extend our in-house Feature Store Platform serving billions of data points in real-time.
• Tune infrastructure (k8s and AWS) and build automations to achieve the best cost-performance.
• Proactively solve technical challenges, discover and build new features, enabling develop efficiency.
• Support our internal users and help with troubleshooting, and turn user problems into scalable solutions.
• Raise our product and technical quality bar, promoting software engineering best practices.

• 5+ years of experience in Software Engineering, out of which 2+ in ML/MLOPS/AI Engineering.
• Experience in leading and delivering complex cross-team projects.
• Production experience with Python, Spark, and Kubernetes.
• Experience in MLOPS and AI ecosystem, and developing end-to-end ML/AI solutions at scale.
• You strive for technical excellence while staying pragmatic to achieve outcomes for the users.

Experience is great, but what we really look for is drive, intelligence, and integrity. So even if you don’t tick every box, please consider applying!

• Accelerate your professional growth with unique career opportunities.
• Enjoy a rewarding salary and stock options, knowing that as Bolt succeeds, so do you.
• Take care of your physical and mental health with our wellness perks.
• Celebrate 5 years at Bolt with a 1-month paid sabbatical to recharge.
• Connect with colleagues at annual company events and smaller team gatherings.
• Balance flexibility and in-person collaboration with our hybrid model, including at least 12 monthly in-office days.

*Some perks may differ depending on your location and role.