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Location: Remote-North & South America Workplace: remote Metabase is the easiest way for people to get insights from their data, from tiny startups who get up and running quickly to major corporations with tens of thousands of users. That's why people love us.   We bring data tools with the elegance and simplicity of consumer products to the crufty world of enterprise business intelligence. We provide an opinionated open source starting point for how companies should measure, analyze and share their data, which is used by tens of thousands of companies. Metabase is looking for an Analytics Engineer to support our team.   This role will be a key part of the operations team, using the disparate data sources we have on our customer base, customer onboarding, and community intelligence to better understand our users, their needs and what we should do to better help our customers.   Things you'll do :   - Iteratively refine our data, build models and help spread data throughout the team to enable self-service analytics - Organize our datasets and do complex transforms using SQL & Python. - Dig into data, answer questions - Teach the others on your team to fish - Collaborate day to day with business users, designers, product managers and engineers - A bit of everything from data ingestion, modeling, analysis, science, and story telling.   Things we're looking for :   - Strong data modeling or integration skills - Extremely strong coding skills using SQL (100+ lines of complex SQL queries/models) or Python (1k+ lines of OOP scripts) - Fluency in expressing business processes using models and charts - 5+ years as an analytics engineer, data analyst, data scientist, data engineer or similar role - BS in CS/CE, Math, Economics or equivalent technical degree preferred - Experience a plus: B2B SaaS, dbt, Postgres/Redshift, Fivetran, dlt, dimensional modeling, data engineering, data science (machine learning), LLM/AI - Candidates who operate in UTC-3 -- UTC-8 Compensation The US base salary range for this role is $95.4K–$190K annually, plus equity and benefits. Compensation is determined by role, level, location, and individual qualifications, including skills, experience, and scope of responsibility. Pay may vary by geographic location and other job-related factors. Benefits We offer meaningful equity and a comprehensive US benefits package, including fully employer-covered medical, dental, and vision insurance (with 75% coverage for dependents), a 401(k) with employer match available to enroll after the first 30 days, flexible and unlimited paid time off including sick time, and an asynchronous, remote-first environment. We're a global team (50% outside the US), fully distributed (from Thailand to California), who get things done asynchronously, with plenty of uninterrupted time, supporting each other to do the best work of our careers. We offer flexibility (define your own schedule and work from wherever you want), autonomy, and an environment that fosters growth, learning, and development. We're relentlessly user-focused and believe in building long-term value, not short-term hacks. And we raised a $30M Series B to take our approach to the next level for years to come.   For U.S. applicants: Metabase participates in the federal E-Verify program, which confirms employment authorization of newly hired U.S. based employees. E-Verify is not used as a tool to pre-screen candidates and is only initiated upon hire.   E-Verify Participation Notice (English/Spanish) Right to Work Notice (English/Spanish)

Location: Limassol Wisebits — is an international IT holding with a strong technical team! Our key product is a high-load video hosting platform used by millions of people worldwide every day. With over 15 years on the market, we’ve built a professional team that values engagement and initiative. If you’re excited about working with a high-load product and want to have an impact on its development, join us! We are looking for an experienced Data Analyst who will help us make key product and business decisions based on data. In this role, you will have the freedom to influence metrics, experiments, and the development of the company’s analytics culture. What you'll be working on: Defining and developing key product metrics. Generating data-driven insights to support product and business decisions. Designing, launching, and analyzing A/B tests, from hypothesis formulation to final results. Monitoring key metrics and identifying anomalies or trends. Writing SQL and Python code to extract, transform, and analyze data. Participating in the implementation of new tracking events and parameters. Working closely with product managers, analysts, designers, data scientists, and data engineers. What we expect from you: 5+ years of experience in analytics. Deep understanding of A/B experiments and statistics. Strong knowledge of Python and SQL. Experience working with ClickHouse and large volumes of data. Ability to translate business questions into metrics and reports. Experience with Google Analytics, Amplitude, or similar tools. Experience with Airflow, preferably together with dbt. Nice to have: Experience implementing data governance practices. Experience using ML approaches in analytics. Experience managing teams, such as data engineers, data scientists, or product analysts. What we offer: No bureaucracy — flexible working conditions. An extended benefits package, including medical insurance, tax coverage, foreign language courses, professional training, and all necessary work equipment. Relocation support: we cover relocation expenses for you and your family, including tickets, visa support, and the first month of accommodation. A friendly international team that values professionalism and collaboration. Here, you won’t just analyze numbers — you’ll have a real impact on the product and the business. Work format: Remote / On-site Salary: From €4,000 net per month. The final compensation level may be higher and depends on relevant experience, skills, and overall match with the role requirements.

Location: Warsaw, PL We are looking for a Data Engineer to design, develop, and optimize our data infrastructure on Databricks. You will architect scalable pipelines using BigQuery, Google Cloud Storage, Apache Airflow, dbt, Dataflow, and Pub/Sub, ensuring high availability and performance across our ETL/ELT processes. You will leverage Great Expectations to enforce data quality standards. The role also involves building our Data Mart (Data Mach) environment and implementing CI/CD best practices. A successful candidate has extensive knowledge of cloud-native data solutions, strong proficiency with ETL/ELT frameworks (including dbt), and a passion for building robust, cost-effective pipelines. Responsibilities Data Architecture & Strategy – Define and implement the overall data architecture on GCP, including data warehousing in BigQuery/Databricks, data lake patterns in Google Cloud Storage, and Data Mart (Data Mach) solutions. Integrate Terraform for Infrastructure as Code to provision and manage cloud resources efficiently. Establish both batch and real-time data processing frameworks to ensure reliability, scalability, and cost efficiency. Pipeline Development & Orchestration – Design, build, and optimize ETL/ELT pipelines using Apache Airflow for workflow orchestration. Implement dbt (Data Build Tool) transformations to maintain version-controlled data models in BigQuery, ensuring consistency and reliability across the data pipeline. Use Google Dataflow (based on Apache Beam) and Pub/Sub for large-scale streaming/batch data processing and ingestion. Automate job scheduling and data transformations to deliver timely insights for analytics, machine learning, and reporting. Event-Driven & Microservices Architecture – Implement event-driven or asynchronous data workflows between microservices. Employ Docker and Kubernetes (K8s) for containerization and orchestration, enabling flexible and efficient microservices-based data workflows. Implement CI/CD pipelines for streamlined development, testing, and deployment of data engineering components. Data Quality, Governance & Security – Enforce data quality standards using Great Expectations or similar frameworks, defining and validating expectations for critical datasets. Define and uphold metadata management, data lineage, and auditing standards to ensure trustworthy datasets. Implement security best practices, including encryption at rest and in transit, Identity and Access Management (IAM), and compliance with GDPR or CCPA where applicable. Scientists & Analytics Enablement – Collaborate with Data Science, Analytics, and Product teams to ensure the data infrastructure supports advanced analytics, including machine learning initiatives. Maintain Data Mart (Data Mach) environments that cater to specific business domains, optimizing access and performance for key stakeholders. Requirements 1. Experience – 3+ years of professional experience in data engineering, with at least 1 year in mobile data 2. Technical Expertise with GCP Stack – Proven track record building and maintaining BigQuery environments and Google Cloud Storage based data lakes. – Deep knowledge of Apache Airflow for scheduling/orchestration and ETL/ELT design. – Experience implementing dbt for data transformations, RabbitMQ for event-driven workflows, and Pub/Sub + Dataflow for streaming/batch data pipelines. – Familiarity with designing and implementing Data Mart (Data Mach) solutions, as well as using Terraform for IaC. 3. Programming & Containerization – Strong coding capabilities in Python, Java, or Scala, plus scripting for automation. – Experience with Docker and Kubernetes (K8s) for containerizing data-related services. – Hands-on with CI/CD pipelines and DevOps tools (e.g., Terraform, Ansible, Jenkins, GitLab CI) to manage infrastructure and deployments. 4. Data Quality & Governance – Proficiency in Great Expectations (or similar) to define and enforce data quality standards. – Expertise in designing systems for data lineage, metadata management, and compliance (GDPR, CCPA). – Strong understanding of OLTP (Online Transaction Processing) and OLAP (Online Analytical Processing) systems. 5. Communication – Excellent communication skills for both technical and non-technical audiences. – High level of organization, self-motivation, and problem-solving aptitude. What we offer Competitive compensation based on your experience and expertise Long-term contract-based collaboration A collaborative and open environment Flexible collaboration arrangements