Company Overview: Lean Tech is a rapidly expanding organization situated in Medellín, Colombia. We pride ourselves on possessing one of the most influential networks within software development and IT services for the entertainment, financial, and logistics sectors. Our corporate projections offer many opportunities for professionals to elevate their careers and experience substantial growth. Joining our team means engaging with expansive engineering teams across Latin America and the United States, contributing to cutting-edge developments in multiple industries. We are looking for a dedicated Data Engineering Sr. Engineer to join our team, to design scalable data pipelines, build robust models, and deliver real-time and batch processing solutions. Ideal for candidates experienced in ETL, Agile, and modern databases like Postgres and ElasticSearch. Join us to innovate on a cutting-edge Event Service Framework. Position Title: Data Engineering Sr. Engineer Location: Remote - Colombia What you will be doing: We seek a Data Engineering Sr. Engineer with robust technical expertise in designing and developing scalable data solutions. The ideal candidate will have hands-on experience in building and managing data pipelines, developing data models, and transforming data for both real-time and batch processing. This role will focus on delivering high-quality, reliable, and scalable data solutions while collaborating with a multidisciplinary team to meet business objectives. Your responsibilities include: Design, develop, and optimize data pipelines and ETL processes using Python and SQL. Collaborate with cross-functional teams to build scalable data models and transformation features tailored to business use cases. Work extensively with AWS services (Lambda, Step Functions, SQS, S3, Athena, DynamoDB) to implement and manage cloud-native data solutions. Leverage Docker/EKS to orchestrate and manage data workloads efficiently. Integrate and manage multiple databases such as Postgres, ElasticSearch, Redis, and OpenSearch (Optional). Ensure high data quality through stringent validation checks and implement self-healing mechanisms for system reliability. Actively participate in Agile ceremonies, including sprint planning, daily standups, and retrospectives, to iteratively deliver prioritized backlog items. Follow best practices for SDLC to ensure secure, maintainable, and efficient code delivery. Collaborate with stakeholders to understand project requirements, prioritize tasks, and deliver end-to-end solutions. Requirements & Qualifications To excel in this role, you should possess: Expertise in Python for data processing and automation. Advanced SQL skills for database management and querying. Experience with GIT for version control. Hands-on experience with EKS/Docker for containerized applications. Expertise with databases such as Postgres, ElasticSearch, and Redis. Strong understanding and implementation experience with AWS services: Lambda Step Functions SQS S3 Athena DynamoDB Proven experience in developing and managing ETL pipelines and transforming data. Ability to deliver end-to-end projects or products. Agile methodology experience and active participation in sprint-based workflows. Solid knowledge of SDLC processes and best practices. Nice to have: Experience with OpenSearch and Graph Database technologies. Knowledge of real-time data processing and event-driven architecture. Familiarity with implementing robust and scalable self-healing systems. Why you will love Lean Tech: Join a powerful tech workforce and help us change the world through technology. Professional development opportunities with international customers. Collaborative work environment. Career path and mentorship programs that will lead to new levels. Join Lean Tech and contribute to shaping the data landscape within a dynamic and growing organization. Your skills will be honed, and your contributions will be vital to our continued success. Lean Tech is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. #J-18808-Ljbffr