Design and build Databricks lakehouse pipelines using PySpark, Spark SQL, and Delta Lake.
Collaborate with frontend, architecture, and clinical teams on APIs and data ingestion.
Ensure GxP, 21 CFR Part 11, HIPAA, and GDPR compliance while optimizing Spark and Delta Lake.
Muttdata builds innovative Data Products and Machine Learning solutions for complex business challenges. They are a fast-growing, remote-first startup with a collaborative, ownership-driven culture that values continuous learning.
Design and deliver data engineering solutions, including data lakehouse buildouts and cloud migrations, for EMEA and US customers.
Lead small delivery teams, mentor junior engineers, and support pre-sales processes to compound impact across the organization.
Work with Apache Spark/Databricks on AWS/Azure, manage customer relationships, and communicate technical concepts to non-technical audiences.
DATAPAO is a data engineering and cloud migration consultancy that helps customers solve complex data puzzles. The company emphasizes a high-transparency culture, open feedback, and a strong community, with a focus on innovation and impact.
Design scalable cloud-native data architectures on Databricks or MS Fabric.
Implement data models, schemas, and storage patterns like lakehouse, Delta, and Parquet.
Collaborate with data architects, analysts, and business stakeholders to ensure data-driven decision making.
Deutsche Telekom IT Solutions, a subsidiary of the Deutsche Telekom Group, provides comprehensive IT and telecommunications services with over 5,300 employees. The company has won awards for educational cooperation and ethical business practices, and it continuously develops its locations in Budapest, Debrecen, Pécs, and Szeged.
Design, develop, and evolve scalable data solutions within cloud environments using Databricks.
Build and optimize data pipelines for large-scale processing with Python, PySpark/Spark, SQL, and Delta Lake.
Apply best practices in data governance, performance, and orchestration while working autonomously with data teams.
The hiring company specializes in data engineering and cloud-based solutions, using Databricks and modern data technologies to build scalable data platforms. It fosters a collaborative culture with continuous learning, innovation, and autonomy for its employees.
Build and operate reliable data infrastructure supporting marketing, payments, and product analytics.
Design and maintain data pipelines using Databricks and Apache Airflow to ensure accurate and timely reporting.
Collaborate with cross-functional teams to translate business needs into scalable data solutions.
Our partner company builds digital products for the mobile app industry, focusing on data-driven marketing and analytics. They offer a collaborative, international environment with a remote-first culture and emphasize continuous learning and professional growth.
Deliver complex data engineering projects for EMEA and US customers, individually or leading small teams.
Support pre-sales, mentor junior engineers, and contribute to hiring best-in-class data talent.
Work remotely in the UK with occasional travel to Budapest for onboarding and quarterly visits.
Datapao is a data engineering and cloud migration consulting company that helps clients solve complex data puzzles using technologies like Apache Spark and Databricks. They are a rapidly growing tech company with a high-transparency culture, emphasizing open feedback and no politics.
Lead high-impact, company-wide data initiatives and mentor junior engineers to foster technical excellence.
Design and architect scalable data solutions, including ELT/ETL pipelines and optimized data models.
Ensure data quality and platform stability through rigorous frameworks and on-call support.
Atlassian is a software company that creates collaboration tools like Jira and Confluence to help teams work together. With a global workforce and a culture centered on teamwork and flexibility, Atlassian empowers employees to do their best work.
Architect the Data Platform by designing internal SDKs and self-service frameworks for distributed engineering teams.
Own platform performance, optimizing the Databricks ecosystem for cost-effectiveness and scalability.
Drive data contracts and governance, implementing schema validation and security standards across the global ecosystem.
G-P offers a SaaS-based Global Employment Platform that enables companies to expand into over 180 countries quickly and efficiently. The company fosters a diverse, remote-first culture where innovation thrives and every contribution is valued.
Architect scalable data solutions using Databricks, Azure Fabric, PySpark, and SQL.
Build and automate end-to-end data pipelines with Azure Data Factory and CI/CD practices.
Mentor junior engineers and partner with stakeholders to align data engineering with business objectives.
Alimentiv is a healthcare technology and clinical research organization supporting gastrointestinal clinical trials and data-driven innovation. It operates with a collaborative global team and a focus on quality, compliance, and technical excellence.
Enable efficient data access by creating and maintaining data pipelines.
Collaborate with ML engineers to design and maintain automation for machine learning training, quality assessment, and model release process.
Identify, design and implement improvements to optimize data delivery and automate manual processes.
Eneba is building an open, safe, and sustainable marketplace for gamers, supporting over 20 million active users. They are a fast-growing company that values data-driven decision-making and fosters a healthy data culture across the organization.
Design, develop, and maintain scalable data pipelines using Microsoft Azure Fabric and Databricks.
Build reliable ETL/ELT processes for structured and unstructured data and ensure production-ready integration solutions.
Collaborate with business stakeholders to translate data requirements into technical solutions and take end-to-end ownership.
This company is a technology organization seeking a Senior Data Engineer to build scalable data pipelines on Azure and Databricks. It offers a fully remote, collaborative environment with global stakeholders and a focus on engineering ownership.
Lead the design and implementation of scalable data architectures for member communications, defining data models, contracts, and lineage.
Build and optimize production-grade data pipelines using Databricks, Apache Spark, PySpark, and SQL, ensuring reliability and performance.
Establish data-quality and governance practices, and partner with Privacy, Compliance, and Risk teams to manage sensitive member data securely.
Oportun is a mission-driven financial services company that provides responsible credit and savings to help members build a better financial future. Since inception, it has provided over $22.7 billion in credit and saved members more than $2.5 billion in interest and fees, reflecting a culture focused on impact and innovation.
You will work under the guidance of the Central Platform Team to build our Databricks engineering framework.
You will establish reusable development patterns and advance our core codebase.
You will use modern data engineering practices and AI-assisted tools to build scalable data solutions.
Talan is an international consulting group specializing in innovation and business transformation through technology. With over 7,200 consultants in 21 countries and a turnover of €850M, they are committed to delivering impactful, future-ready solutions.
Design, build, and operate data products that transform raw data into customer-facing insights.
Develop large-scale ETL/ELT pipelines using Apache Spark and PySpark, with workflow orchestration via Airflow or AWS Step Functions.
Work across AWS and GCP infrastructure, incorporating AI-assisted search and LLM-powered features in production.
The partner company builds data-driven intelligence products from unstructured social and public data. It operates with a remote-first, async-friendly culture that emphasizes high autonomy and low bureaucracy.
Lead design and implementation of enterprise data pipelines within Microsoft Fabric.
Mentor data engineers and establish best practices for data engineering.
Ensure data platform security, availability, and performance requirements are met.
Rackner is a software consultancy focused on building mission-critical systems for the U.S. government. The company provides a creative and forward-thinking environment with growth opportunities and modern perks.
Design and drive the execution of a scalable, cloud-native target-state architecture for the data platform.
Define architectural patterns for scalable automated data ingestion and deliver hands-on proof-of-concepts using SQL, PySpark, and Serverless Python.
Drive governance, security, and engineering excellence across all platform components, ensuring alignment with business and product strategies.
G-P is a SaaS-based Global Employment Platform that enables clients to expand into over 180 countries. Our diverse, remote-first teams foster innovation and value every contribution, empowering employees with flexibility and resources.
Translate legacy Databricks notebook logic into modern ELT patterns using Python and PySpark, ensuring data contract preservation and reverse-view strategies.
Build scalable ingestion pipelines with YAML configurations and orchestrate automated DAG generation via workflow schedulers, applying quality assertions and migration validation.
Collaborate with business Data Stewards to align dependencies, negotiate refactoring scope, and validate migrated outputs for production systems.
CI&T helps large companies transform AI potential into real business impact with AI deployment, AI-native execution, and tech-integrated business solutions. With 30 years of tech transformation experience and over 8,000 CI&Ters in 25+ countries, we accelerate innovation through agentic SDLC, application modernization, Data & AI, martech, and business strategy.
Design, build, and improve a scalable data platform to provide data solutions for product teams.
Develop and manage automated data pipelines using cloud-based and on-premise technologies.
Ensure data quality, lineage, and observability across the stack while collaborating with product and business teams.
lemlist is a bootstrapped sales engagement platform that grew from $0 to $57M ARR in 8 years. It is a profitable B2B SaaS company trusted by 40,000+ sales teams worldwide.
Design end-to-end data pipelines to collect, process, transform, and load data into cloud environments.
Lead and mentor a team of data engineers while collaborating with client stakeholders on data requirements.
Build and optimize ETL processes to ensure data quality, integrity, and actionable insights.
Nimble Gravity is a team of outdoor enthusiasts, adrenaline seekers, and experienced growth hackers who love solving hard problems. They believe the right data can transform and propel growth for any organization.
Lead the complete data chain for the Foundation Pod, covering ingestion, Bronze, Silver, Gold layers, and the Power BI semantic layer.
Build, optimize, and maintain scalable ETL/ELT data pipelines and Gold certified datasets to drive BI and analytics.
Implement robust Data Lakes, Data Warehouses, and integration layers aligned with the global data strategy.
We help large enterprises transform the potential of AI into real business impact with AI Deployment, AI-native execution, and tech-integrated business solutions. We are 8,000 CI&Ters across more than 25 countries, collaborating to build solutions with real impact.