Big Data Tech Lead

KIS is looking for a talented Tech Lead who is aiming to work on an IT project, working on the maintenance and improvement of a big and complex data pipeline. This opportunity has high visibility and high growth so it is key to have diverse experiences in various areas of computing like data management, reports creation, support, backend API development, cloud computing, as well as team and client management experience to be successful in this role. If you think this fits your profile, we certainly look forward to talking to you!
As a Tech Lead, you will own both the technical and delivery strategy of complex data platforms, ensuring reliability, scalability, and long-term sustainability while leading and developing high-performing teams.

• Lead and manage teams working on large, complex, end-to-end data platforms and pipelines.
• Develop deep understanding of the structure, semantics, and business meaning of complex data landscapes.
• Own the technical architecture of the platform, designing scalable, secure, and cost-efficient cloud-based data solutions.
• Translate business requirements into technical strategies and execution plans for projects of any size.
• Create and communicate technical artifacts, including architecture diagrams, data models, data dictionaries, and technical design documentation.
• Act as the primary technical authority, unblocking the team and guiding complex technical decisions.
• Define delivery plans, estimates, and priorities; clearly communicate plans, progress, and risks to the team and to clients.
• Ensure high-quality delivery at both code and platform levels, enforcing engineering, data quality, and operational standards.
• Perform and oversee peer code reviews, promoting clean code, reusable patterns, testing, and strong Git practices.
• Drive continuous improvement initiatives to enhance platform reliability, efficiency, scalability, and delivery speed.
• Anticipate technical, delivery, and operational risks; escalate issues proactively and plan mitigations.
• Own responsibilities beyond development, including infrastructure, monitoring, production support, maintenance, and operational processes.
• Establish and enforce observability practices (monitoring, logging, alerting, SLOs/SLAs) and lead incident response when needed.
• Work across teams, providing architectural guidance and governance beyond the immediate team.
• Mentor and develop engineers, fostering technical excellence, ownership, and career growth.
• Participate in talent assessment decisions to ensure strong team composition.

• 5+ years of professional experience in software or data engineering.

• Proven experience leading teams on complex IT or data platform projects.
• Strong experience with end-to-end big data pipelines (batch, streaming, or hybrid).
• Advanced proficiency in SQL (queries, performance tuning, indexing, partitioning).
• Strong programming skills in Python or similar languages, following clean and modular engineering practices.
• Deep understanding of cloud architecture, including compute, storage, networking, identity, and cost optimization.
• Expertise in data platform architecture, including modern paradigms such as Lambda, Kappa, microservices, and event-driven pipelines.
• Strong background in data modeling (dimensional, normalized, and data vault models).
• Ability to independently deliver and oversee tasks of any complexity.
• Excellent business and technical acumen, with the ability to connect technical decisions to business impact.
• Proven experience defining and managing CI/CD pipelines, automation, and release strategies.
• Strong experience debugging and resolving complex production issues in data platforms.
• Excellent communication skills, with confidence driving discussions and providing clear updates to clients and stakeholders.
• Experience working with agile methodologies (e.g., Scrum).
• Strong organizational skills, including prioritization, estimation, and management of competing priorities.
• Advanced English proficiency for client-facing communication and documentation.
• Experience defining organization-wide data quality frameworks, data contracts, and anomaly detection.
• Hands-on experience with data governance, lineage, cataloging, and access control.
• Familiarity with regulatory and compliance requirements (e.g., GDPR, HIPAA).
• Experience leading technology evaluations and Proofs of Concept (PoCs).
• Experience providing cross-team architectural governance or acting as a platform steward.
• Background influencing engineering culture at scale, including documentation, observability, and review practices.
• Must be based in Latin America.

Originally posted on Himalayas