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 Are you passionate about building modern, scalable data platforms that power enterprise analytics? We're looking for a Senior Data Engineer to play a key role in the global implementation and ongoing evolution of our Databricks data platform. This is an exciting opportunity to shape the foundation of our enterprise data strategy while mentoring a growing team of engineers and partnering with stakeholders around the world. As a Senior Data Engineer, you'll serve as one of the technical leaders on our Data Platform team, helping design, implement, and optimize enterprise-scale data solutions that enable business intelligence, advanced analytics, and AI initiatives. In this role, you will: - Lead the implementation and continued enhancement of our global Databricks data platform. - Design, build, and optimize scalable ETL/ELT pipelines for structured and semi-structured data. - Develop modern data models, data warehouses, and data marts to support enterprise analytics. - Collaborate closely with data scientists, analysts, business partners, and IT teams to translate business requirements into scalable technical solutions. - Improve data quality, governance, security, and platform reliability. - Optimize data workflows for performance, scalability, and cost efficiency. - Provide technical mentorship to junior and mid-level data engineers while helping establish engineering best practices. Qualifications - Bachelor's degree in Computer Science, Engineering, Information Systems, or a related field required. - 5+ years of hands-on experience with SQL and Python. - 5+ years of experience working with cloud platforms (Azure, AWS, or GCP). - 5+ years of experience with modern data warehousing technologies such as Databricks, Snowflake, Redshift, or BigQuery. - Strong experience designing and building enterprise-scale data pipelines and ETL/ELT solutions. - Solid understanding of data modeling, governance, and security principles. - Excellent communication skills with the ability to collaborate across technical and business teams. Requirements - Databricks Certification (preferred). - Experience with Spark, Kafka, or other distributed processing frameworks (preferred). - Experience with DevOps and CI/CD practices (preferred). - Experience supporting machine learning and AI data initiatives (preferred). Benefits - This is more than a traditional data engineering role—it's an opportunity to help build the next generation of our global data platform. - You'll join a growing Data Platform team where you'll: - Lead enterprise-wide Databricks initiatives. - Work alongside a collaborative team while mentoring developing engineers. - Influence technical direction and engineering best practices. - Partner with business leaders across Finance, Sales, Supply Chain, Manufacturing, and Corporate functions. - Help drive digital transformation across a global organization. The salary range for this position is $110,200-$144,700. Factors such as scope and responsibilities of the position, candidate's work experience, education/training, job-related skills, internal peer equity, as well as market and business considerations may influence base pay offered. This salary will be subject to a geographic adjustment (according to a specific city and state), if an authorization is granted to work outside of the location listed in this posting.

Role Description The Principal Databricks Architect will shape and scale our Databricks-based data science and AI platform, and to lead where our practice is heading: a governed, self-service environment that lets data science teams move from idea to production with minimal friction. As the technical leader of the platform, this individual brings design thinking to mature the platform as a product—designing reusable capabilities, patterns, and guardrails that empower actuarial, data science, and analytics teams to independently develop, train, deploy, and operate models and AI agents. The ideal candidate pairs deep architectural expertise with a strong enablement mindset, engaging directly with diverse data science communities to understand their workflows and remove barriers to adoption. They will modernize our platform around the latest Databricks capabilities—Unity Catalog governance, Mosaic AI and Agent Bricks, Genie, Lakeflow, and Lakebase—while ensuring interoperability with our Snowflake enterprise data platform through open formats such as Apache Iceberg. This is a highly visible role that sets technical direction, champions frictionless developer experience, enforces least-privileged access and data governance, and enables global, cost-efficient deployment of AI in compliance with data sovereignty requirements. Qualifications - Bachelor’s Degree in Arts/Sciences (BA/BS) Computer Science or equivalent education and experience - Required - 10+ years progressive experience in enterprise-level IT functions - Required - 7+ years experience in managing large enterprise data initiatives and teams - Required - 5+ years architecting and operating enterprise-grade data and AI/ML platforms, with hands-on Databricks and Apache Spark experience on a major cloud (AWS preferred; Azure or GCP) - Required Requirements - Modern Databricks Expertise: Deep knowledge of the Databricks Data Intelligence Platform—Unity Catalog, Delta Lake/Iceberg, Lakeflow/Delta Live Tables, MLflow, Model Serving, AI Agent Framework/Agent Bricks, Lakebase, and Genie—plus lakehouse architecture, ETL/ELT, and infrastructure-as-code (Terraform, Databricks Asset Bundles) - Required - Data Science Enablement: Demonstrated success building self-service platform capabilities and developer experiences that empower data science teams, along with a ModelOps track record covering lifecycle management, versioning, governance, and deployment automation - Required - Consulting & Communication: Strong consulting, stakeholder management, and communication skills, with a track record of influencing senior leadership and driving technology adoption - Required - Innovation & Initiative: Demonstrated ability to drive innovation, introduce contemporary practices, and lead technology transformations - Required - Thought Leadership: Ability to define and communicate architecture vision, roadmaps, and best practices to both technical and non-technical audiences - Preferred - Continuous Improvement: Passion for learning, sharing knowledge, and staying ahead of industry trends in data and AI - Preferred - Platform-as-a-Product Mindset: Passion for delivering frictionless, self-service experiences and measurable business value—treating internal data science teams as customers and continuously improving their journey from prototype to production - Preferred - Interoperability Experience: Familiarity integrating Databricks with Snowflake and other engines via open standards (Apache Iceberg, Unity Catalog/Lakehouse federation) to minimize data duplication and governance gaps - Preferred - Availability for cross-time-zone meetings - Preferred Benefits - Gain valuable knowledge from and experience with diverse, caring colleagues around the world. - Enjoy a respectful, welcoming environment that fosters individuality and encourages pioneering thought. - Join the bright and creative minds of RGA, and experience vast, endless career potential. - Compensation Range: $126,710.00 - $188,840.00 Annual - Annual bonus plan and eligibility for long-term equity incentive plan. - Full range of health, retirement, and other employee benefits.