Senior Data Engineer
Lean Solutions Group
14 días+
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Descripción de la vacante
Lean Solutions Group is seeking a Data Engineer to join our Data Services team in Colombia. This role involves advanced data modeling, SQL engineering, and BI enablement within a streaming architecture environment.
The ideal candidate will have expert SQL proficiency, experience with data platforms like Snowflake, and familiarity with technologies such as DBT and Kafka. Join us to contribute to innovative data solutions that significantly impact our global client base.
Formación
- Deep SQL expertise and strong grasp of database internals.
- Familiarity with cloud environments (AWS, GCP, Azure).
- Ability to manage schema evolution challenges effectively.
Responsabilidades
- Design, build, and maintain advanced data models using DBT.
- Develop and optimize complex SQL queries and stored procedures.
- Monitor and tune Materialize clusters for optimal performance.
- Collaborate with BI engineers to define supporting models.
Conocimientos
Expert-level SQL proficiency
Experience with streaming-enabled databases
Familiarity with Kafka
Hands-on experience with DBT
Understanding of relational database concepts
Experience with Snowflake
General software engineering skills
Herramientas
Materialize
PostgreSQL
Docker
Kubernetes
Descripción del empleo
Company Overview
Lean Tech is a forward-thinking technology consultancy built on a foundation of excellence, innovation, and impact. We partner with organizations worldwide to deliver transformative engineering solutions that drive measurable business outcomes. Our strength lies in providing highly skilled nearshore talent who embody ownership, technical mastery, and a collaborative mindset. At Lean Tech, we cultivate a culture of continuous improvement, autonomy, and professional growth, empowering our teams to thrive in dynamic environments. We specialize in designing and implementing scalable data platforms, resilient pipelines, and advanced analytics ecosystems that unlock the full potential of organizational data. By joining Lean Tech, you become part of a diverse, global engineering community that embraces creativity, problem-solving, and modern technologies to tackle complex challenges. Together, we are shaping the future of data-driven innovation and redefining how businesses leverage technology to achieve success.
Position Overview
We are seeking a Data Engineer to join our Data Services / Data Products team. This role is central to bridging advanced data modeling, expert-level SQL engineering, and BI enablement. Unlike traditional BI or pipeline-focused positions, this opportunity demands deep SQL expertise, a strong grasp of database internals, and familiarity with cloud infrastructure concepts to optimize query performance, with an increasing emphasis on real-time, event-driven data processing within streaming architectures. You will transform raw application data into curated, high-performance models using DBT, Materialize, and Snowflake. These models will serve as the backbone for BI engineers and stakeholders, powering dashboards, reports, and mission-critical data products. Operating within a modern, streaming-aware ecosystem, you will support and reason about real-time data flows from CDC and Kafka, understanding how data changes propagate across systems and impact downstream consumers, while collaborating closely with Data Platform and BI Engineering teams to deliver end-to-end workflows that are reliable, scalable, and efficient.
Key Responsibilities
● Design, build, and maintain advanced data models and transformations using DBT across Materialize and Snowflake.
● Develop and optimize complex SQL queries, views, and stored procedures with a focus on compute cost, memory usage, and indexing strategies.
● Translate BI and business requirements into scalable semantic models and curated tables for real-time reporting.
● Monitor and tune Materialize clusters, ensuring optimal resource usage and performance.
● Troubleshoot upstream data issues in collaboration with Data Platform engineers, addressing CDC connectors, pipelines, and message flows.
● Participate in schema design, data quality assessments, and governance best practices.
● Collaborate with BI engineers to define models that support analytical and reporting needs.
● Support streaming-enabled architectures, integrating CDC, Kafka, and Materialize with Snowflake.
● Contribute to infrastructure tasks, reviewing IaC deployments, containerized flows, and system logs.
● Drive continuous improvement in pipeline reliability, performance, cost optimization, and documentation.
Required Skills & Experience
● Expert-level SQL proficiency, including query optimization, indexing, and database engine behavior.
● Experience with streaming-enabled databases (e.g., Materialize or similar technologies), or strong hands-on experience with streaming data processing and incremental SQL in near real-time systems.
● Familiarity with Kafka, JSON message patterns, and real-time systems.
● Hands-on experience with DBT for modeling and transformation.
● Strong understanding of relational database concepts and query plans.
● Experience with modern data warehouses such as Snowflake.
● Proficiency in SQL-based stored procedures/functions (PostgreSQL preferred; Oracle/SQL Server valuable).
● General software engineering skills, including log analysis and deployment reasoning.
● Ability to manage schema evolution challenges effectively.
Nice to Have
● Experience in cloud environments (AWS, GCP, Azure, Oracle).
● Python scripting for validation, automation, or pipeline support.
● Familiarity with Docker, Kubernetes, and IaC tools (Terraform, CloudFormation).
● Exposure to CDC technologies (FiveTran, HVR) and ability to debug pipeline issues related to CDC and ingestion workflows.
● Basic dashboarding experience with Power BI or similar tools.
● Knowledge of observability practices in cloud environments.
Soft Skills
● Strong analytical mindset with attention to performance trade-offs.
● Excellent communication skills for cross-functional collaboration.
● Curiosity and adaptability to learn new tools quickly.
● Ownership-driven problem-solving with attention to detail.
● Team-oriented mindset to support upstream and downstream partners.
Why You Will Love Working with Us
At Lean Tech, you will join a powerful tech workforce committed to changing the world through innovation. We offer professional development opportunities with international clients, a collaborative environment, and mentorship programs designed to accelerate your career growth. Your contributions will directly shape the data landscape of a dynamic, growing organization. We
celebrate diversity, foster inclusion, and believe in empowering every employee to reach their full potential.
Lean Tech is a forward-thinking technology consultancy built on a foundation of excellence, innovation, and impact. We partner with organizations worldwide to deliver transformative engineering solutions that drive measurable business outcomes. Our strength lies in providing highly skilled nearshore talent who embody ownership, technical mastery, and a collaborative mindset. At Lean Tech, we cultivate a culture of continuous improvement, autonomy, and professional growth, empowering our teams to thrive in dynamic environments. We specialize in designing and implementing scalable data platforms, resilient pipelines, and advanced analytics ecosystems that unlock the full potential of organizational data. By joining Lean Tech, you become part of a diverse, global engineering community that embraces creativity, problem-solving, and modern technologies to tackle complex challenges. Together, we are shaping the future of data-driven innovation and redefining how businesses leverage technology to achieve success.
Position Overview
We are seeking a Data Engineer to join our Data Services / Data Products team. This role is central to bridging advanced data modeling, expert-level SQL engineering, and BI enablement. Unlike traditional BI or pipeline-focused positions, this opportunity demands deep SQL expertise, a strong grasp of database internals, and familiarity with cloud infrastructure concepts to optimize query performance, with an increasing emphasis on real-time, event-driven data processing within streaming architectures. You will transform raw application data into curated, high-performance models using DBT, Materialize, and Snowflake. These models will serve as the backbone for BI engineers and stakeholders, powering dashboards, reports, and mission-critical data products. Operating within a modern, streaming-aware ecosystem, you will support and reason about real-time data flows from CDC and Kafka, understanding how data changes propagate across systems and impact downstream consumers, while collaborating closely with Data Platform and BI Engineering teams to deliver end-to-end workflows that are reliable, scalable, and efficient.
Key Responsibilities
● Design, build, and maintain advanced data models and transformations using DBT across Materialize and Snowflake.
● Develop and optimize complex SQL queries, views, and stored procedures with a focus on compute cost, memory usage, and indexing strategies.
● Translate BI and business requirements into scalable semantic models and curated tables for real-time reporting.
● Monitor and tune Materialize clusters, ensuring optimal resource usage and performance.
● Troubleshoot upstream data issues in collaboration with Data Platform engineers, addressing CDC connectors, pipelines, and message flows.
● Participate in schema design, data quality assessments, and governance best practices.
● Collaborate with BI engineers to define models that support analytical and reporting needs.
● Support streaming-enabled architectures, integrating CDC, Kafka, and Materialize with Snowflake.
● Contribute to infrastructure tasks, reviewing IaC deployments, containerized flows, and system logs.
● Drive continuous improvement in pipeline reliability, performance, cost optimization, and documentation.
Required Skills & Experience
● Expert-level SQL proficiency, including query optimization, indexing, and database engine behavior.
● Experience with streaming-enabled databases (e.g., Materialize or similar technologies), or strong hands-on experience with streaming data processing and incremental SQL in near real-time systems.
● Familiarity with Kafka, JSON message patterns, and real-time systems.
● Hands-on experience with DBT for modeling and transformation.
● Strong understanding of relational database concepts and query plans.
● Experience with modern data warehouses such as Snowflake.
● Proficiency in SQL-based stored procedures/functions (PostgreSQL preferred; Oracle/SQL Server valuable).
● General software engineering skills, including log analysis and deployment reasoning.
● Ability to manage schema evolution challenges effectively.
Nice to Have
● Experience in cloud environments (AWS, GCP, Azure, Oracle).
● Python scripting for validation, automation, or pipeline support.
● Familiarity with Docker, Kubernetes, and IaC tools (Terraform, CloudFormation).
● Exposure to CDC technologies (FiveTran, HVR) and ability to debug pipeline issues related to CDC and ingestion workflows.
● Basic dashboarding experience with Power BI or similar tools.
● Knowledge of observability practices in cloud environments.
Soft Skills
● Strong analytical mindset with attention to performance trade-offs.
● Excellent communication skills for cross-functional collaboration.
● Curiosity and adaptability to learn new tools quickly.
● Ownership-driven problem-solving with attention to detail.
● Team-oriented mindset to support upstream and downstream partners.
Why You Will Love Working with Us
At Lean Tech, you will join a powerful tech workforce committed to changing the world through innovation. We offer professional development opportunities with international clients, a collaborative environment, and mentorship programs designed to accelerate your career growth. Your contributions will directly shape the data landscape of a dynamic, growing organization. We
celebrate diversity, foster inclusion, and believe in empowering every employee to reach their full potential.
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