Be the first Senior Data Scientist to join our Central Data Team and build our data science function from the ground up, leading the charge in developing advanced data products that will directly fuel our Product & Marketing strategies. Design and develop custom-built solutions, including LLMs, predictive models for forecasting, recommendation systems, and causal inferences. Contribute to building Remote’s data science culture and processes.
Seeking an English-fluent Data Engineer, based in Latin America, available to work remotely. The ideal candidate would enhance and maintain the infrastructure powering our analytics and data products, ingest new data from files, APIs, and external databases into a centralized data store. You would also implement and enforce data governance policies, ensuring adherence to best practices in data security, integrity, privacy, and regulatory compliance.
Transition legacy systems to a cloud-native, modern data stack leveraging tools such as Informatica, Airflow, Postgres and modern technologies like Snowflake, dbt , BigQuery , Looker, CI/CD, Git, Databricks, PowerBI , Datadog and Grafana. Build innovative, scalable, and reliable data products that support Kinaxis’ strategic goals. Partner with internal business stakeholders from different business units and cross-functional teams to design and deliver tailored data solutions.
We’re looking for a Data Engineer with hands-on experience in Snowflake to support upcoming client initiatives. You’ll play a key role in designing, building, and optimizing secure data pipelines and cloud data warehouse solutions. This position is ideal for someone who thrives in fast-moving environments, values clean architecture, and enjoys collaborating closely with both technical and non-technical stakeholders.
Shape our data infrastructure, develop frameworks, and establish architectural patterns that enhance our entire data engineering team's efficiency. Contribute to building and maintaining our data processing and storage pipelines/workflows while ensuring robust security, scalability, and innovation through AI integration. Take ownership of our data systems to make them world class.
Lead the Data Engineering function, creating an environment of exceptional technical execution. As leader of Data Engineering at Headspace you will be at the leading edge of the AI revolution and have meaningful opportunities to profoundly impact the future of mental health care. You will be responsible for leading and growing a team of talented engineers, spearheading our data strategy and architecture.
You will be pivotal in transforming marketing, sales, and user behavior data into actionable intelligence that directly fuels user acquisition, engagement, monetization, and retention strategies. As a key partner to the Marketing, Growth, and Product teams, you'll leverage your analytical expertise to uncover opportunities, measure impact, and help shape the company's growth trajectory through data-driven decision-making.
As a part of the Data Analytics function at Cribl, you will lead a team of data professionals dedicated to supporting our Revenue, Marketing, and Finance teams. You will oversee the business intelligence system, data analysis, and data strategy, playing a critical role in driving data-informed decision-making and fostering a culture of analytics excellence. Your ability to balance strategic vision with operational execution will be critical.
As a Solution Architect – Advanced Analytics, you will lead the design and delivery of cloud-native analytics architectures for enterprise clients. This role requires strong consultative and business communication skills. You’ll work with clients to assess needs, define solutions, and lead implementation across the data lifecycle. You’ll play a key role in articulating the business value and ROI of these solutions.
We’re seeking a hands-on Analytics Engineering Lead to head our data infrastructure and modeling efforts. In this role you will manage a small team while also contributing directly as an individual contributor. You’ll collaborate closely with our analytics, data science, and ML teams to deliver high-quality, reliable data to the whole company.