• Manage and optimise Snowflake data warehouses. • Overhaul Snowflake warehouse performance through materialisation strategies, dynamic tables, and clustering optimisation. • Build scalable ETL/ELT pipelines using dbt, Airflow, Fivetran, and AWS DMS. • Build ingestion pipelines using DMS and Fivetran. • Develop modelling layers in dbt using medallion architecture principles. • Transform raw data into clean, reliable, and business-ready models using dbt and AI-assisted tooling for documentation and testing. • Integrate data from multiple sources, including CRM systems, payment platforms, gaming platforms, and other operational systems. • Own initiatives focused on data quality improvements and monitoring, including anomaly detection and automated alerting. • Monitor and optimise platform performance, cost efficiency, and security. • Work closely with cross-functional teams across product development, data, operations, and analytics functions. • Collaborate with the data science team and support colleagues with reporting and analytics activities when required. • Support the organisation’s move towards real-time data ingestion and ETL using technologies such as DMS, Kafka, and Kinesis. • Help mentor other engineers within the team. • Contribute to the team's AI strategy and promote effective use of AI tools across engineering workflows. • Produce and maintain clear, comprehensive documentation to support scalability, transparency, and long-term platform sustainability. • Communicate effectively with both technical and non-technical stakeholders and proactively raise blockers when encountered.

• Design, develop, and maintain scalable data pipelines and integration solutions within the Azure ecosystem • Build and support enterprise data platforms that consolidate information from multiple source systems • Develop ETL/ELT processes to ingest, transform, validate, and distribute business-critical data • Contribute to data modelling, data quality, and governance initiatives • Support Master Data Management (MDM) processes and ensure consistency across systems • Work with structured and semi-structured data from ERP, business applications, APIs, databases, and external sources • Collaborate with business and technical stakeholders to translate requirements into scalable data solutions • Participate in deployment, testing, monitoring, and continuous improvement activities • Contribute to CI/CD pipelines, automation, and DevOps best practices • Actively participate in Agile ceremonies and team collaboration

As a Data Engineer, you will be responsible for building and maintaining scalable, reliable data infrastructure that powers the organization's data platform. You will develop ETL/ELT pipelines for both batch and real-time data processing, integrate data from multiple sources, optimize data warehouse models, and ensure data quality, performance, and scalability. Working closely with Data Scientists, Analytics Engineers, BI specialists, and IT/DevOps teams, you will enable data-driven decision-making and support key business functions in a fast-growing international e-commerce environment. •Build and maintain ETL/ELT pipelines (batch and streaming) •Work with event-driven architectures and real-time data processing •Integrate multiple data sources via APIs and replication •Design and optimize data warehouse models •Set up monitoring, logging, and alerting •Continuously improve performance, scalability, and reliability

Role Description This Sr. Data Engineer – Fabric serves as a senior technical leader within the Data Engineering organization and is responsible for designing, implementing, and optimizing enterprise-scale data solutions utilizing Microsoft Fabric. This role leads the design and development of modern data architectures leveraging OneLake, Lakehouses, Warehouses, Data Pipelines, Dataflows Gen2, Notebooks, and related Azure technologies. The Sr. Data Engineer - Fabric collaborates with business stakeholders, analytics teams, architects, and leadership to deliver reliable, scalable, and secure data solutions that support operational reporting, advanced analytics, machine learning, and enterprise decision-making. In addition to hands-on engineering responsibilities, this role provides technical leadership and mentorship to other Data Engineers, establishes engineering standards and best practices, participates in platform governance initiatives, and serves as a subject matter expert for Microsoft Fabric and modern data platform technologies. This role reports to the Sr. Data Engineering & Report Visualization Manager. What This Role Does - Collaborates with cross-functional teams to understand data and analytical requirements and translates them into effective Microsoft Fabric–based data solutions. - Mentors and provides technical leadership to Data Engineers through code reviews, design reviews, knowledge-sharing sessions, and engineering best practices. - Establishes and maintains data engineering standards, reusable frameworks, development patterns, and operational best practices to improve consistency and scalability across the data platform. - Leads root cause analysis and resolution efforts for critical production issues impacting enterprise data pipelines, reporting solutions, and platform operations. - Reviews and provides guidance on solution designs, architecture decisions, and implementation approaches to ensure alignment with enterprise standards and best practices. - Designs, develops, and maintains end-to-end data ingestion and transformation processes using Microsoft Fabric OneLake, Lakehouses, Data Pipelines, Dataflows Gen2, and Notebooks. - Formats, cleanses, and stores data in a structured manner to ensure data quality and accessibility for reporting and analysis, following Medallion Architecture. - Works closely with reporting and analytics teams to ensure datasets are accurate, well-modeled, and optimized for Power BI and other analytical workloads. - Creates comprehensive documentation for data pipelines, processes, and solutions. - Participates in data governance activities to ensure data integrity, security, and compliance. - Utilizes source control to manage and track changes to data pipelines and codebase. - Provides level II/III support to troubleshoot and resolve data-related issues and inquiries. - Provides ancillary support for Machine Learning (ML) and Artificial Intelligence (AI) processes. - Evaluates emerging technologies, industry trends, and architectural patterns related to data engineering, analytics, artificial intelligence, and cloud platforms and provides recommendations for adoption. - Manages and optimizes Microsoft Fabric platform performance by monitoring capacity utilization, query performance, Lakehouse and Warehouse workloads, Delta table maintenance (OPTIMIZE/VACUUM), data partitioning, storage consumption, and pipeline execution to ensure scalable, reliable, and cost-effective data operations. - Develops and maintains monitoring, alerting, and observability solutions for Microsoft Fabric pipelines, notebooks, Lakehouses, Warehouses, semantic models, and related data platform components to ensure operational reliability and rapid issue resolution. - Performs other duties as assigned. Qualifications - Bachelor's degree in computer science, information technology, or a related field (or equivalent experience). - A minimum of six (6) years of proven experience in data engineering, ETL development, and data warehousing. - Demonstrated experience leading complex data engineering projects from architecture and design through implementation and operational support. - Demonstrated ability to lead through influence, collaboration, and technical expertise, including mentoring Data Engineers and cross-functional technical teams, leading initiatives and workstreams, and driving successful cross-functional outcomes. - Experience establishing engineering standards, governance processes, development frameworks, and operational best practices. - Advanced troubleshooting and performance optimization experience across cloud data platforms, distributed processing frameworks, and enterprise data solutions. - Strong hands-on experience with Microsoft Fabric, including OneLake, Lakehouses, Data Pipelines, Dataflows Gen2, and/or Notebooks. - Solid understanding of Medallion Architecture, Delta Lake concepts, data modeling, and modern analytics patterns. - Experience with data governance, data quality, and data security frameworks and standards. - Solid grasp of Continuous Integration Continuous Delivery (“CI/CD”), including source control, deployment pipelines, and release management practices. - Experience with Git-based source control and collaborative development workflows. - Expertise in integrating Fabric solutions with Power BI, Azure services, and external data sources. - Experience monitoring and tuning cloud-based data platforms for performance, scalability, and cost optimization. - Experience with Apache Spark and PySpark within Microsoft Fabric. - Expertise in developing data pipelines to support Machine Learning (ML) and/or Artificial Intelligence (AI) tools is a plus. - Excellent verbal and written communication skills, presentation, problem-solving skills and attention to detail. - Self-starter with strong organizational and time management skills, self-directed and able to handle multiple priorities with demanding timeframes. - Ability to work independently and collaboratively with colleagues and staff to create a high-quality, results-driven, team-oriented, fast-paced environment. - Demonstrated ability to use discretion, make sound decisions, and maintain confidentiality. - Willingness and ability to work flexible hours. - Proficiency in MS Office (including Excel, Outlook, PowerPoint, Visio, & Word) and modern communication tools for virtual teams (e.g., MS Teams, Slack). Physical Demands - Sitting, standing, and walking (95-100%) - Keyboarding (70-90%) - Viewing computer monitor, tablet, and cell phone requiring close vision (70-90%) Work Environment - 100% Remote: Work environment is at home. Compensation $150,000 - $160,000 plus 5% determined by competitive market analysis and internal equity considerations. Final compensation will be based on the candidate’s qualifications, experience, and business needs. For details on our comprehensive benefits program, visit www.clearcaptions.com/careers to explore our total rewards package. Intrigued to learn more? When you apply for this role, your information will be personally reviewed by our talent acquisition team (not by a robot). You can expect to hear back from us if we think there could be a fit and what next steps look like. Disclaimer The above information in this description has been designed to indicate the general nature and level of work performed by employees within this classification. It is not designed to contain or be interpreted as a comprehensive inventory of all duties, responsibilities, and qualifications required of employees to do this job.