Senior Data Engineer
1 мес. назад
LATAMWorldwideSenior
data pipelinesdata modelinganalytics infrastructuresoftware engineering
Senior Data Engineer role focused on building scalable data systems and analytics infrastructure to support data science and business decision-making.
Обязанности
- We are seeking a Senior Data Engineer to join a cross-functional team working on scalable data systems and analytics infrastructure.
- This is an individual contributor role focused on building, maintaining, and optimizing data pipelines and data models that power analytics and business-critical decision-making. The role requires a strong technical generalist mindset, combining software engineering principles with deep data expertise.
- You will work closely with Data Science, Data Ops, and business stakeholders to ensure data is accurate, accessible, and structured for self-service analytics. The ideal candidate is someone who enjoys working with complex datasets, simplifying systems, and building scalable data infrastructure from the ground up.
Требования
- 5+ years of experience in software engineering, with at least 3 years focused on data engineering or data infrastructure
- Strong expertise in SQL and working with relational databases
- Experience building and maintaining scalable data pipelines
- Proficiency in at least one general-purpose programming language (Python preferred)
- Experience with modern data stack tools (e.g., Spark, DBT, Airflow/Dagster)
- Strong debugging and problem-solving skills in complex systems
- Experience working with cloud data warehouses (BigQuery, Snowflake, or Databricks)
- Ability to design data systems that support analytics and business intelligence
- Strong communication skills and ability to work cross-functionally
- Experience documenting and simplifying complex systems
Будет плюсом
- Experience with backend engineering and API development
- Experience with Infrastructure as Code (IaC) tools
- Exposure to system design for customer-facing or high-scale platforms
- Familiarity with analytics-heavy environments and data-driven products
- Experience working with large-scale, real-world datasets (e.g., transactions, behavioral data)
Другое
- is an operating partner for startups and growth-stage companies, helping them turn ambition into execution.
- We support founders and leadership teams with product engineering and global staffing, from early prototypes and MVPs to scaling high-performing teams. Our vetted talent across LATAM and Asia embeds directly into client teams, operating as true extensions rather than external vendors.
- With over 8 years working in venture-backed ecosystems, is trusted to accelerate delivery, scale teams efficiently, and support companies as they reach their next milestone.
- Own, build, maintain, and optimize scalable data pipelines
- Design and implement data architectures that support analytics and operational use cases
- Work with large, complex datasets to meet evolving business requirements
- Ensure data quality, reliability, and performance across systems
- Apply best practices for developing specialized datasets for analytics and modeling
- Continuously improve data workflows, pipelines, and infrastructure
- Develop a deep understanding of core data models and business logic
- Partner with Data Science and Data Ops teams to maintain trusted, well-documented datasets
- Enable self-service analytics by structuring and organizing data effectively
- Support analytical workflows and downstream consumption of data
- Assist analysts with query development and dataset preparation
- Work with a wide range of stakeholders to gather requirements and translate them into technical solutions
- Communicate complex technical concepts clearly to both technical and non-technical audiences
- Collaborate closely with engineering, analytics, and product teams
- Contribute to documentation and knowledge sharing across teams
- Contribute to the design of scalable and maintainable systems
- Optimize data delivery and infrastructure for performance and scalability
- Support integration across multiple data platforms and tools
- Maintain and improve existing systems, including search and indexing solutions
- Independently troubleshoot complex systems and resolve data-related issues
- Perform root cause analysis and implement long-term fixes
- Improve system reliability and performance through monitoring and optimization
- Ensure stability and efficiency of data platforms
- SQL for querying, transformation, and data modeling
- Python or other general-purpose programming languages (e.g., JavaScript/TypeScript, Java, C#, Go, Scala)
- Experience with data pipeline tools such as Spark and DBT
- Data warehouses such as BigQuery, Snowflake, or Databricks
- Workflow orchestration tools such as Airflow or Dagster
- Experience handling large-scale data processing and transformations
- Familiarity with batch and/or streaming data systems
- Cloud platforms such as GCP or AWS
- Infrastructure as Code tools (Terraform, Pulumi, or CloudFormation)
- Experience designing scalable and maintainable systems
- Experience with backend engineering and web services is a plus
- Familiarity with analytics and data visualization ecosystems
- Exposure to transaction, receipt, or viewership data is beneficial
- Ownership mindset: Ability to take responsibility and drive systems end-to-end
- Technical versatility: Strong foundation as a software engineer with data expertise
- Problem-solving focus: Ability to navigate ambiguity and solve complex challenges
- Communication skills: Clear and effective collaboration across teams
- Execution-driven: Ability to move quickly and deliver results in a fast-paced environment
- Continuous improvement: Desire to refine systems, processes, and technical approaches