• Develop and test automation for data aggregation and consolidation • Participate in technical decisions together with the tech lead and the team.

Role Description The Data Analytics Engineer supports the data team to drive innovation in data analytics and ensuring the reliability and scalability of our data systems. - Execute a comprehensive data strategy aligned with Digistore24’s objectives. - Support to manage the full data domain: architecture, technology choices, policies, procedures, cost monitoring, alerting, etc. - Ensure the data foundation is performant and scalable to meet business needs. - Enhance analytics capabilities and drive the development of predictive models and data visualization tools. - Communicate and align with various teams on business and technical needs. - Perform on clear goals and objectives, ensuring alignment with organizational priorities. - Ensure the accuracy, reliability, and integrity of data analytics processes and outputs. - Implement best practices for data acquisition, integration, transformation, and delivery. - Stay current with emerging technologies and trends in data engineering. - Serve as a subject matter expert on data analytics and engineering topics, providing guidance and support as needed. Qualifications - Fast learner with the ability to connect business and technical perspectives. - Utilize cloud environments (AWS, Azure, preferably GCP) to manage and process data. - Work with data warehousing solutions such as BigQuery, Redshift, and Snowflake to ensure efficient data storage and retrieval. - Comfortable working across different teams, managing multithreading, and handling ambiguity. - Employ ETL tools like dbt, SQLMesh, and GCP DataForm to transform and prepare data for analysis. - Ability to build and maintain dashboards, create interactive visualizations, and generate actionable business insights using Power BI, Tableau, Looker or similar tool. - Proficient in both project management and operational work, with the ability to delegate and coach. - Self-motivated, capable of making independent decisions, and solving problems innovatively. - Excellent verbal, written, and interpersonal communication skills. - Experienced in computer science, data science, engineering, or a related field. - Proven experience in a data analyst or data engineering role. - Fluent in both written and spoken English to communicate with our international team. - Experience in ERP migrations, tax datamarts, or procurement automation; collaborate cross-functionally to enable self-service analytics for non-technical users. - Familiarity with event tracking and product analytics tools (e.g., Amplitude, Mixpanel, GA4, Segment, Snowplow). - Experience building and analyzing funnels, cohorts, and experiments to inform product roadmap and go-to-market strategy. - Ability to balance statistical rigor with speed, clearly communicating trade-offs and uncertainty. Requirements - This position is NOT for you if you have less than 3 years of experience in relevant data positions. - View software development as only the activity of code writing. - Cannot write high quality code without a modern framework or need Windows to develop. - Casually make changes to codes without understanding their consequences. - Can’t take ownership and need to discuss every detail with your product manager or colleagues. - Do not have the ambition to continuously expand your knowledge. - Do not identify with our values. - Are looking for a B2B contract: we can NOT offer this. - Are NOT based in Europe (continent). Benefits - Play a crucial role in shaping our cutting-edge projects in a collaborative work environment. - Work in our partner's coworking spaces (max. 3 days a week) or in your home office, as long as you can guarantee uninterrupted internet access. - Regular further education. - The stability of an extremely successful German high-tech company that is funded by its successful product and not by investors. - Outcome focused teams and a culture of direct feedback. - Modern equipment: MacBook. - International, collaborative team with strong cohesion. - Spectacular team events in various European countries. - Autonomy from day one. - Work in your team on a first-name basis, without a dress code, and at eye level. - Flexible working hours from Mondays to Fridays.

Role Description Join us to start Caring. Connecting. Growing together. You’ll enjoy the flexibility to telecommute* from anywhere within the U.S. as you take on some tough challenges. - Design, develop, and deploy AI-powered solutions to address complex business challenges with an emphasis on the responsible use of AI. - Architect and optimize complex ETL processes and data pipelines using Databricks (Spark, SQL, Python) or other enterprise-scale integration tools to ensure high-performance processing of large-scale datasets. - Evaluate emerging trends in ETL frameworks and AI to inform solution design and drive strategic innovation within the analytics platform. - Use enterprise-approved AI tools to automate data engineering workflows, streamline ETL maintenance, and drive continuous improvement in engineering velocity. - Implement advanced data modeling techniques, such as star schemas and incremental loads, to ensure data integrity and scalability across all ETL layers. - Build and maintain executive-level dashboards and semantic models in Power BI, ensuring seamless data flow from backend ETL processes to end-user visualizations. - Partner with product and business leaders to translate complex business requirements into robust, automated data integration solutions. - Lead technical coordination within a global delivery model, ensuring consistency and quality of ETL standards across onshore and offshore teams. Qualifications - Bachelor's degree or equivalent experience. - 6+ years of experience in analytics engineering, business intelligence, or data engineering roles delivering enterprise-scale analytics solutions. - 5+ years of Cloud experience (Azure, GCP, AWS, or OCI). - 5+ years of experience in programming languages such as Python, Java, etc. - 4+ years of hands-on experience using Databricks (Spark, SQL, Python, notebooks) or other major ETL platforms to build and optimize large-scale data pipelines. - 4+ years of experience in data modeling (star schemas, semantic modeling, incremental loads, large datasets) and advanced SQL. - 1+ years of experience delivering AI-driven analytics or data solutions. Requirements - Healthcare industry experience, specifically in clinical or real-time analytics. - Experience with ETL orchestration tools (e.g., Airflow, Azure Data Factory) and managing data lineage in governed environments. - Experience developing AI-driven automations or integrating large language models (LLMs) into data products and ETL workflows. - Experience with Power BI, Tableau or other visualization tools, including advanced DAX, Power Query, and semantic modeling. - Demonstrated experience working in global delivery models with effective onshore-offshore collaboration. - Proven ability to solve complex technical problems with a focus on data processing efficiency and system scalability. Benefits - Comprehensive benefits package. - Incentive and recognition programs. - Equity stock purchase. - 401k contribution (all benefits are subject to eligibility requirements).

Role Description We are seeking a highly skilled and motivated Data Engineer with experience in MQTT and IoT core expertise. The ideal candidate will be responsible for designing and implementing scalable data pipelines, optimizing data workflows, and enabling actionable insights from large-scale building systems data. - Perform data exploration and analysis to identify trends, anomalies, and optimization opportunities. - Implement cost-effective data solutions using cloud-native tools and services. - Ensure high-quality documentation of data models, pipelines, and system architecture. - Collaborate with cross-functional teams including product managers, building engineers, and software developers. - Follow best engineering practices including unit testing, code reviews, and adherence to SOLID/KISS principles. Qualifications - Proficiency in Python for data engineering and scripting. - Strong experience in data exploration and analysis using tools like Pandas, SQL, or Jupyter. - Proven ability to design complex data solutions that handle large-scale, heterogeneous data sources. - Experience with cost optimization in cloud or on-premise data environments. - Excellent documentation skills and ability to communicate technical concepts clearly. - Familiarity with software engineering best practices (unit testing, SOLID, KISS, CI/CD). Requirements - Exposure to IoT protocols (BACnet, Modbus, MQTT) and edge computing. Preferred Qualifications - Bachelor's or Master's degree in Computer Science, Engineering, or a related field. - Experience working in smart buildings, energy management, or facility automation domains.