• Design, develop, and maintain robust, scalable ETL/ELT data pipelines using Python, SQL, and data processing frameworks including dbt, Matillion, and AWS services. • Implement data quality checks, monitoring, and alerting across all data pipelines to ensure data integrity and reliability. • Optimize existing pipelines for performance, cost-efficiency, and error handling. • Contribute to the design and maintenance of InStride’s data warehouse and data lake solutions, including schema design, data modeling, and indexing strategies in Amazon Redshift. • Ensure data security, HIPAA compliance, and proper handling of protected health information (PHI) within all data infrastructure. • Work closely with data analysts, data scientists, and business intelligence engineers to understand their data requirements and deliver reliable, high-quality data access. • Troubleshoot and resolve complex production data issues with urgency and root-cause rigor. • Develop and maintain clear documentation for data models, pipelines, and data sources to enable self-service analytics. • Participate in code reviews and contribute to technical discussions, bringing a constructive and detail-oriented perspective. • Stay current on emerging data technologies and tools, bringing relevant insights to the team.

Role Description Integrarte a un equipo de datos para diseñar, desarrollar y operar pipelines ETL/ELT en Azure, garantizando la ingesta, transformación y disponibilidad de datos para consumidores de negocio y modelos analíticos. El rol implica responsabilidad técnica en la implementación de soluciones con Azure Data Factory, Azure Databricks y ecosistemas de almacenamiento (Blob Storage, Data Lake) aplicando buenas prácticas de calidad, rendimiento y gobernanza de datos. Responsibilities - Diseñar y desarrollar pipelines de ingestión y transformación de datos utilizando Azure Data Factory y Azure Databricks. - Implementar procesos ETL/ELT con Apache Spark y PySpark para procesamiento por lotes y en tiempo casi real. - Modelar y optimizar consultas SQL y estructuras de datos para consumo analítico y reporting. - Gestionar y organizar datos en Azure Blob Storage y Azure Data Lake (Gen2), definiendo particionamiento, formatos y políticas de retención. - Construir pipelines reproducibles, parametrizables y observables; instrumentar logging, métricas y alertas. - Colaborar con equipos de ciencia de datos, BI y producto para definir contratos de datos, SLAs y requisitos de calidad. - Automatizar despliegues y pruebas de pipelines; aplicar control de versiones y prácticas CI/CD para artefactos de datos. - Garantizar cumplimiento de políticas de seguridad y privacidad en el manejo de datos sensibles. - Documentar arquitecturas, pipelines y runbooks; transferir conocimiento al equipo y participar en on-call rotativo cuando aplique. Qualifications - Experiencia comprobable como Data Engineer (mín. 3 años) trabajando con Azure Data Factory y Azure Databricks. - Dominio de Apache Spark y PySpark para procesamiento distribuido y optimización de jobs. - Sólidos conocimientos de SQL: modelado, tuning y optimización de consultas. - Experiencia en diseño e implementación de pipelines ETL/ELT y en integración de datos. - Conocimiento práctico de Azure Blob Storage y Azure Data Lake (Gen2), incluyendo formatos como Parquet/Delta Lake. - Familiaridad con herramientas de orquestación, monitorización y CI/CD aplicadas a datos. - Inglés técnico: nivel intermedio (lectura de documentación y comunicación con equipos técnicos). - Residir en Argentina. Bonus Points - Experiencia con Delta Lake, optimizaciones de storage y compaction. - Conocimientos en seguridad y gobernanza de datos: RBAC, Data Catalog, políticas de enmascaramiento. - Familiaridad con Python avanzado y librerías de ingeniería de datos (pandas, numpy, airflow o equivalentes). - Experiencia con performance tuning de Spark y troubleshooting de jobs en Databricks. - Certificaciones Azure relacionadas con datos (DP-203, Azure Data Engineer Associate) o Databricks. - Experiencia en entornos cloud a gran escala y en trabajo ágil con equipos multidisciplinarios. Selection Process - Recruiting screen - Entrevista técnica - Entrevista con el cliente - Oferta Benefits - Envía tu solicitud y únete a nosotros para impulsar soluciones de datos robustas y escalables. - Para postular: - Envía tu CV a través de nuestro portal. - Completa tu perfil en talentconnect.ai. - Participa en una entrevista inicial utilizando inteligencia artificial. - Al completar estos pasos estarás más cerca de sumarte a nuestro equipo.

Role Description We are looking for a Data Engineer Analyst to contribute to the design and implementation of scalable, domain-oriented data solutions for a high-impact enterprise initiative. You will work within a specific data domain — such as Ingestion, Customer Data, Enrichment, or Marketing Signals — ensuring high-quality, reliable data pipelines that power analytics and business-critical workflows. You may work 100% remotely from anywhere in Mexico! - Contribute to the design and development of scalable data pipelines on AWS (Glue, S3, Athena, Step Functions). - Build and optimize batch and streaming ingestion pipelines, including CDC-based architectures. - Support the design and implementation of data models aligned with business and analytics needs. - Ensure data quality, reliability, and performance across pipelines and datasets. - Collaborate with cross-functional teams to align technical solutions with business requirements. - Apply best practices in data engineering, including modular design, reusability, and governance. - Leverage AI-assisted development tools to improve productivity and code quality. - Proactively identify risks, bottlenecks, and optimization opportunities across data workflows. Qualifications - Bachelor's degree in Computer Science, Data Engineering, Software Engineering, or equivalent field. - Hands-on experience with the AWS ecosystem, including Glue, S3, Athena, and Step Functions (required). - Solid proficiency in Python and PySpark for data pipeline development (required). - Experience with Snowflake or similar cloud data warehouse platforms (plus). - Understanding of data pipeline architecture and design patterns. - Exposure to CDC (Change Data Capture) patterns and streaming ingestion. - Experience with data modeling for analytics and reporting use cases. - Familiarity with AI-assisted development tools (plus). - Strong problem-solving skills and ability to work effectively in collaborative, agile environments. - English: Advanced (required for effective communication with global teams). Requirements - 3+ years of experience in Data Engineering or related disciplines, with hands-on work building and maintaining data pipelines on cloud platforms such as AWS. Benefits - Learning Opportunities: - Certifications in AWS (we are AWS Partners), Databricks, and Snowflake. - Access to AI learning paths to stay up to date with the latest technologies. - Study plans, courses, and additional certifications tailored to your role. - Access to Udemy Business, offering thousands of courses to boost your technical and soft skills. - English lessons to support your professional communication. - Travel opportunities to attend industry conferences and meet clients. - Mentoring and Development: - Career development plans and mentorship programs to help shape your path. - Celebrations & Support: - Special day rewards to celebrate birthdays, work anniversaries, and other personal milestones. - Company-provided equipment. - Flexible working options to help you strike the right balance. - Other benefits may vary according to your location in LATAM. For detailed information regarding the benefits applicable to your specific location, please consult with one of our recruiters.

Role Description As a Senior Data Engineer at Nearform your main task will be designing, building, and maintaining scalable data platforms, pipelines, and warehouses using SQL, Python, Spark, and other relevant technologies. You will play a key role in building efficient data solutions, optimizing performance, and ensuring seamless data integration. However as you’ll likely work on a variety of projects your responsibilities may also include: - Designing, building, and optimizing data pipelines and ETL processes for large-scale data ingestion and transformation. - Developing and maintaining data platforms and warehousing solutions to support analytics and business intelligence needs. - Implementing scalable data storage solutions and ensuring high availability and performance. - Enhancing performance in data processing workflows for maximum speed and scalability. - Collaborating with data scientists, analysts, and stakeholders to understand business needs and translate them into data engineering solutions. - Ensuring data quality, governance, and compliance across all systems. - Supporting CI/CD processes for data pipeline deployments and implementing best practices in DevOps for data workflows. - Conducting code reviews and enforcing best practices in version control, automation, and testing. - Assisting with defining structured source code management and deployment processes. - Working with and supporting Technical Leaders in project execution and timely delivery. - Collaborating with client teams. Qualifications - Significant experience delivering at a Senior Engineer level, specialising in Data engineering. Our Seniors typically have at least 6 years’ commercial experience. - Practical experience of delivering in an agile environment. - Practical experience and knowledge of developing real-world solutions. - Extensive hands-on experience in some of the following technologies: Databricks, SQL, Python, and Spark for large-scale data processing. - Strong expertise in data warehousing technologies (e.g., Snowflake, Redshift, BigQuery, or similar). - Experience with distributed data processing frameworks (Spark, Hadoop, or similar). - Deep understanding of ETL processes, data modeling, and schema design. - Strong experience with cloud-based data solutions (AWS, Azure, GCP) and data lake architectures. - Experience with automation, CI/CD for data pipelines, and Infrastructure as Code (IaC). - Deep understanding of versioning control tools - e.g. Git. - Experience building software collaboratively using pull requests and code reviews. - Familiarity with data governance, security, and compliance best practices. - Excellent communication and collaboration skills. - Professional proficiency in English. Benefits - Annual Company Bonus - We all help Nearform to hit company goals so we all receive a share of the profits on an annual basis in line with company performance. - Work Remotely and Flexibly - We have a genuine dedication to work/life balance. Our flexible working culture allows you to work around what matters - school run, no problem! - Paid Time Off Package - We offer an annual leave of 24 days plus public holidays. We also offer sick leave, marriage leave and many more. - Remote Working Allowance - Every 2 years, you will have a budget of up to €1250 to help you set up a comfortable and productive workspace in addition to your essential equipment provided by Nearform when you join. - Training and Development Allowance - We understand the importance of continuously learning so we offer an allowance of up to €1000 you can use to upskill yourself. - Healthcare - It’s important to always take care of your health, so we offer additional private healthcare here at Nearform. If you wish to learn more about the plan offered feel free to reach out to our team. - Pension & Insurances - We offer a pension match of up to 5% and Income Protection and Death in Service for peace of mind. Company Description Nearform is an independent team of data & AI experts, engineers, and designers who build intelligent digital solutions and capability at pace. We create AI-enabled solutions that enhance digital experiences, empower developers, and deliver measurable results. In these ways, we partner with ambitious enterprises to deliver enduring impact. Our deep expertise in solving the world’s most complex digital problems, along with our collaborative, people-first approach, enables enterprises to build breakthrough products and modernise legacy systems by unleashing the power of AI. Today, our team of 500 experts in 20+ countries is trusted by leading enterprises including Lululemon, Puma, Sun Life, Starbucks, Travelex, Virgin Media 02, and Walmart.