Role Description Join us as a Data Architect / Lead and play a key role in shaping the data foundation behind our next generation of analytics and AI solutions. In this position, you’ll: - Define the architecture vision for our modern data ecosystem. - Guide a growing team of Data Engineers. - Build cloud-native platforms that unlock enterprise-wide insights. - Work closely with business and technology leaders. - Influence strategic decisions. - Drive the adoption of advanced analytics and Generative AI across the organization. Responsibilities - Lead & Strategize - Lead and mentor Data Engineers, fostering innovation and continuous improvement. - Own the data architecture vision aligned with business goals. - Partner with executives and stakeholders to turn strategic needs into scalable data solutions. - Architect & Build - Design and optimize modern data platforms using Azure Data Lake, Databricks, SQL Server, Microsoft Fabric, and NoSQL. - Build robust, scalable data pipelines across diverse data sources. - Implement strong data quality, governance, and security practices. - Support advanced analytics, machine learning, and AI-based solutions. - Enable Insights - Build solutions that deliver accurate, timely insights for decision-makers. - Collaborate on Power BI dashboards and executive reporting. - Integrate Generative AI into insight-generation workflows. Qualifications - Bachelor’s degree in Computer Science, Data Engineering, or related field. - 4+ years in data engineering, architecture, or analytics roles. - Experience leading Data Engineering teams in enterprise settings will be a plus. - Strong skills in Azure data services, Databricks, SQL, NoSQL, and Microsoft Fabric. - Hands-on Power BI and enterprise reporting experience. - Proven ability to build data pipelines and enforce data quality. - Excellent communication skills, especially with executive stakeholders. - Relevant certifications (Azure Data Engineer, Databricks, Fabric Analytics, etc.) are a plus. Benefits - Work format: Remote or in a comfortable office in Lviv - you choose. - Development: Personal development plan, mentoring, English and Polish language courses. - Stability: Official employment from day one, annual review of salary and career prospects. - Corporate culture: Events that unite the team and a space where everyone can be themselves.

Role Description PwC Poland’s Cloud & Digital team supports global cloud projects across Cloud Strategy, Migrations, Data Analytics, and DevOps. We help clients adopt cloud infrastructure, modernize data platforms, and optimize operations. This hybrid role is based in Warsaw with flexible working options. - Building data platforms (data warehouses, lakes, lakehouses) using Azure Databricks, MS Fabric, Azure Data Factory. - Designing data flows using medallion architecture and supporting data migrations from legacy systems. - Conducting data assessments with Data Modelers/Analysts and addressing data quality issues. - Working with senior stakeholders to gather requirements and support modern data architecture design. - Supporting Data Governance activities, especially around MDM and Data Quality. - Understanding Data Science/Analytics use cases in industries like Consumer Goods, Retail, Manufacturing, or Financial Services. Qualifications - 3 years of experience in Data Engineering or related fields (BI, Data Science). - Hands‑on experience with Databricks, Snowflake, BigQuery, MS Fabric. - Experience building data warehouses/lakehouses with Azure Data Factory / Synapse. - Skills in PySpark/Python and SQL. - Some exposure to CI/CD (Azure DevOps, Jira). - B2+ English and ability to prepare technical documentation. - Experience using modern tech and AI tools in daily work. Requirements - Cloud certifications (Azure/AWS/GCP) and Data Governance certifications. - Training via platforms like Coursera/Udemy/Datacamp. - Knowledge of data modelling (e.g., Kimball), Data Strategy, Data Quality, and MDM. - Experience with Agile (Scrum), ML/GenAI use cases, or Agentic AI for data automation. - Work with senior stakeholders (e.g., CDOs) in Manufacturing, Consumer Goods, or Financial Services. Benefits - Remote or in a comfortable office in Lviv - you choose. - Personal development plan, mentoring, English and Polish language courses. - Official employment from day one, annual review of salary and career prospects. - Events that unite the team and a space where everyone can be themselves.

Role Description We are seeking a Senior Cloud Data Engineer who will manage the existing cloud data platform to make it more scalable, reliable, and cost efficient. This position will be full-time and remote. What You’ll Do - Analyze and understand existing data warehouse implementations to support migration and consolidation efforts. - Reverse-engineer legacy stored procedures (PL/SQL, SQL) and translate business logic into scalable Spark SQL code within Databricks notebooks. - Design and develop data lake solutions on AWS using S3 and Delta Lake architecture, leveraging Databricks for processing and transformation. - Build and maintain robust data pipelines using ETL tools with ingestion into S3 and processing in Databricks. - Collaborate with data architects to implement ingestion and transformation frameworks aligned with enterprise standards. - Evaluate and optimize data models (Star, Snowflake, Flattened) for performance and scalability in the new platform. - Document ETL processes, data flows, and transformation logic to ensure transparency and maintainability. - Perform foundational data administration tasks including job scheduling, error troubleshooting, performance tuning, and backup coordination. - Work closely with cross-functional teams to ensure smooth transition and integration of data sources into the unified platform. - Participate in Agile ceremonies and contribute to sprint planning, retrospectives, and backlog grooming. - Triage, debug and fix technical issues related to Data Lakes. - Maintain and manage code repositories like Git. Qualifications - 8–12 years of experience in data engineering, data warehousing, or big data platform development. - 5+ years of hands-on experience with Databricks including Spark, Delta Lake, and performance optimization. - 4+ years of experience designing and implementing cloud-based data lake or lakehouse architectures on Databricks. - Strong expertise in Spark technologies including Spark SQL, PySpark, or Scala. - Advanced SQL and PL/SQL skills with the ability to interpret and refactor legacy stored procedures. - Strong understanding of data modeling techniques including Star Schema, Snowflake, and modern Lakehouse modeling approaches. - Proficiency in at least one programming language (Python, Scala, Java). - Hands-on experience with data modeling and warehouse design principles. - Experience designing enterprise-scale ETL/ELT pipelines and ingestion frameworks. - Strong understanding of performance tuning, partitioning strategies, and cost optimization for large-scale data platforms. - Experience implementing CI/CD pipelines and DevOps practices for data engineering workflows. - Bachelor’s degree in computer science, Information Technology, Data Engineering, or related field. - Experience working in Agile environments and contributing to iterative development cycles. Requirements - Databricks Professional or Associate Cloud Certification. - Experience with enterprise data governance, metadata management, and data catalog platforms. Company Description CAI is a global services firm with over 9,000 associates worldwide and a yearly revenue of $1.3 billion+. We have over 40 years of excellence in uniting talent and technology to power the possible for our clients, colleagues, and communities. As a privately held company, we have the freedom and focus to do what is right—whatever it takes. Our tailor-made solutions create lasting results across the public and commercial sectors, and we are trailblazers in bringing neurodiversity to the enterprise.

Role Description We are searching for an ambitious go-getter who welcomes the challenge of meeting the needs of a hyper-growth startup. As a Sr. Data Engineer, you will be at the heart of Growth Protocol’s data infrastructure, playing a foundational role in building the systems that power our AI platform. Your work will directly influence product features, client outcomes, and strategic business decisions. You will collaborate with Data Scientists, Backend Engineers, Client IT, and business stakeholders to build and maintain scalable pipelines that serve billions of rows of structured and unstructured data weekly, enabling high-impact insights across multiple industries. Objectives of the Role - Collaboration - Work closely with Data Scientists to translate business and ML requirements into robust data workflows. - Ensure timely delivery of clean, reliable data to support model development and production features. - Technical Development - Engineer and manage scalable ETL architecture using Airflow, Snowpark, Cloud Run, and Apache Beam. - Design and implement a high-performance data infrastructure for seamless processing and integration. - Extract data from diverse online platforms. - Operationalize machine learning models, focusing on deployment, reliability, and performance. - Data Connectivity - Partner with client IT teams to identify the most efficient and secure methods for data ingestion including Snowflake Sharing, Databricks Delta Sharing, Private Link, and VPN. - Work alongside the Platform Engineering team to define requirements for secure networking paths that support high-performance data transfers. - Perform end-to-end testing of client connections to ensure data integrity and connectivity. - Integrate customer databases with our platform. - Monitoring and Reliability - Create and manage real-time monitoring systems for data ingestion and transformation pipelines. - Proactively identify and resolve issues to maintain high levels of system reliability and data integrity. Qualifications - 5+ years of experience in Data Engineering. - Bachelor's degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience. - Experience building data pipelines with robust unit and integration testing. - Proficiency in distributed computing frameworks including Apache Beam and Spark. - Functional understanding of enterprise networking including VPC peering, Private Link, and VPNs, with the ability to troubleshoot connectivity in a cloud environment. - Hands-on experience operationalizing ML models in production. - Familiarity with ML/AI, NLP, and Data Science workflows including MLFlow. - Deep understanding of ETL workflows, data modeling, and data architecture. - Strong debugging and problem-solving skills. - Excellent communication skills and experience collaborating across teams. Preferred Qualifications - Experience working on enterprise products serving Fortune 500 clients across Financial Services, Industrials, and Consumer Products. - Prior startup experience. - Interest in current events, market dynamics, and emerging technologies. - Experience creating Agent Skills. - Familiarity with APIs and web scraping for data collection. - Familiarity with Graph Databases. Tech Stack - Languages: Python, TypeScript - Frameworks: Apache Beam, Spark, FastAPI, Airflow - Cloud: Google Cloud Platform - Data: Elasticsearch, Snowflake, Databricks, Neo4J, PostgreSQL, MongoDB, GCS - Infrastructure and DevOps: Docker, Terraform, GitHub Actions, Cloud Run - Frontend: Next.js Benefits - Competitive compensation and equity in a rapidly growing company. - 100% company-paid health, dental, and vision insurance plus 401(k). - Pet-friendly office.