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Chief Data Software Engineer

Remote in Colombia, Mexico
Data Software Engineering
& 10 others
Colombia

We are in search of a highly motivated and visionary Chief Data Software Engineer to design, strategize, and architect scalable data solutions on modern cloud platforms like BigQuery or Databricks.

In this role, you will lead and inspire teams of Data Engineers and Data Architects, set the strategic direction for enterprise data infrastructure, and champion an automation-first and innovation-driven culture. The Chief Data Software Engineer will be accountable for aligning data engineering initiatives with organizational goals, driving technical excellence, and unlocking impactful business insights.

Responsibilities
  • Define and lead the strategic roadmap for data engineering, focusing on scalability, efficiency, and innovation in line with organizational objectives
  • Build and oversee a high-performing team of Data Engineers, Data Architects, and Technical Leads, fostering leadership and technical growth across all levels
  • Design and implement enterprise-scale data pipeline architectures using Python, SQL, and modern data engineering practices, ensuring automation-first development
  • Drive enterprise-wide initiatives for building and maintaining robust batch and real-time data processing solutions using BigQuery, Databricks, Apache Airflow, and DBT
  • Architect and champion end-to-end data infrastructure solutions, embedding CI/CD and DevOps automation principles into development processes
  • Establish and enforce best practices for clean, reusable, and scalable code while enabling resilience and fault tolerance in enterprise data systems
  • Oversee the integration of data workflows with full-stack development, bridging business applications, machine learning workflows, and advanced analytics
  • Implement advanced monitoring, observability, and alerting systems for proactive identification and resolution of issues in data infrastructure
  • Collaborate with executive leadership and cross-functional teams to tackle complex technical challenges and align data engineering practices with business growth strategies
  • Develop and oversee self-service tools, APIs, and automation frameworks to democratize data accessibility and usability across the organization
  • Optimize the performance, security, and cost-efficiency of enterprise data systems and pipelines deployed on cloud platforms
  • Develop and implement enterprise-grade data governance, ensuring secure, compliant, and quality-driven data handling across the organization
Requirements
  • BS/MS/PhD in Computer Science, Software Engineering, or a related technical field
  • 7+ years of experience in production-grade data engineering and software development with demonstrated expertise in enterprise architectures and automation practices
  • 2+ years of leadership experience (team up to 10 FTEs)
  • Deep expertise in software engineering principles, including version control (Git), CI/CD workflows, testing frameworks, and agile methodologies
  • Proven expertise in Python, SQL, and modern cloud data platforms such as Databricks and BigQuery
  • Extensive experience designing and managing cloud-native architectures on AWS, GCP, or Azure, with a primary focus on complex data ecosystems
  • Proficiency with containerization and orchestration technologies like Docker and Kubernetes, enabling scalable and efficient workflows
  • Advanced capability to implement and manage distributed pipeline orchestration tools such as Apache Airflow, DBT, or similar platforms
  • Expert-level skills in building enterprise-grade APIs, microservices, and event-driven architectures for data workflows and analytics solutions
  • Comprehensive understanding of enterprise DataOps and DevOps practices, including the use of infrastructure-as-code (Terraform, Pulumi) and automation workflows
  • Significant knowledge of event streaming platforms such as Kafka or Kinesis for large-scale, real-time data solutions
  • Proven success in creating and deploying frameworks for automated data governance, quality assurance, and enterprise data products
  • Exceptional communication skills, with English proficiency at a C1 level or higher
Nice to have
  • Experience with advanced analytics platforms, data visualization tools (e.g., Looker, Tableau), or customer data platforms like Amplitude or Segment
  • Background in architecting and operationalizing MLOps workflows for machine learning models and AI-driven solutions
  • Expertise in real-time analytics systems, data streaming technologies, and low-latency application design
  • Proficiency in Linux/Unix system administration and advanced shell scripting
  • Advanced skills using cloud-native DevOps tools and frameworks for CI/CD, performance monitoring, and infrastructure automation solutions
Benefits
  • International projects with top brands
  • Work with global teams of highly skilled, diverse peers
  • Healthcare benefits
  • Employee financial programs
  • Paid time off and sick leave
  • Upskilling, reskilling and certification courses
  • Unlimited access to the LinkedIn Learning library and 22,000+ courses
  • Global career opportunities
  • Volunteer and community involvement opportunities
  • EPAM Employee Groups
  • Award-winning culture recognized by Glassdoor, Newsweek and LinkedIn