Position Overview
We are seeking a Data Engineer to join our Data Services / Data Products team, playing a pivotal role that bridges advanced data modeling, expert-level SQL engineering, and BI enablement. Your primary responsibility will be to transform raw application data into curated, high-performance models using tools like DBT, Materialize, and Snowflake. These models will serve as the foundation for BI engineers and stakeholders to power critical dashboards, reports, and data products. This is not a traditional BI or pipeline development role; it requires deep SQL expertise, a strong understanding of database internals, and familiarity with cloud infrastructure concepts to optimize query performance. You will work within a modern, streaming-aware data ecosystem, supporting real-time data flows from CDC and Kafka, and collaborating closely with Data Platform and BI Engineering teams to navigate end-to-end data workflows.
Key Responsibilities
Design, build, and maintain advanced data models and transformations using DBT across Materialize and Snowflake environments.
Develop and optimize expert-level SQL queries, views, and stored procedures, focusing on compute cost, memory usage, and advanced indexing strategies.
Translate business and BI requirements into scalable semantic models and curated tables to support real-time dashboards and reporting.
Monitor, tune, and optimize Materialize cluster usage, managing compute resource sizing and memory performance.
Troubleshoot and resolve upstream data issues by collaborating with Data Platform engineers on components such as CDC connectors, pipelines, or message flows.
Participate in schema design, data quality assessments, and the implementation of data governance best practices.
Collaborate with BI engineers to define data models that effectively support analytical and reporting requirements.
Analyze and support streaming-enabled architectures, including data flows from CDC, Kafka, and Materialize into Snowflake.
Support infrastructure tasks by understanding Infrastructure as Code (IaC) deployments, reviewing containerized flows, and exploring system logs.
Engage in continuous improvement efforts focused on pipeline reliability, performance tuning, cost optimization, and technical documentation.
Required Skills & Experience
Expert-level SQL proficiency, including query optimization, indexing strategies,
understanding of database engine behavior, and the ability to write complex transformations.
Hands-on experience with DBT for data transformation and modeling.
Strong understanding of relational database concepts, including schemas, views, indexes, and query plans.
Experience working with modern data warehouses such as Snowflake.
Solid understanding of SQL-based stored procedures or functions, preferably
in PostgreSQL, with experience in other engines like Oracle or SQL Server
also being valuable.
Experience with streaming-enabled databases like Materialize, including an
understanding of compute resource usage and cluster sizing.
Ability to debug and troubleshoot upstream pipeline issues related to CDC,
connectors, or ingestion workflows.
Familiarity with streaming and real-time systems concepts, such as Kafka and JSON message consumption patterns.
Experience working in modern cloud environments (AWS, GCP, Azure, or
Oracle).
General software engineering skills, including the ability to understand data
flows, investigate logs, and reason about deployment components.
Familiarity with container technologies such as Docker and orchestration tools
like ECS or Kubernetes from a conceptual standpoint.
Conceptual understanding of Infrastructure as Code (IaC) tools, such as Terraform or CloudFormation.
Ability to handle schema evolution challenges, including adjusting models
when upstream schemas change (e.g., new fields, nullability changes,
removed fields).
Nice to Have Skills
Experience with Python for data validation, automation, or pipeline support
Scripts.
Exposure to infrastructure-as-code tools (Terraform, CloudFormation).
Understanding of CDC technologies (FiveTran, HVR).
Basic experience building dashboards using Power BI or similar tools (not a
primary requirement but beneficial).
Experience working with streaming databases or event-driven architectures.
Knowledge of observability practices: logs, metrics, and resource monitoring in
cloud environments.
Soft Skills
Strong analytical mindset with the ability to reason about systems, data flows,
and performance trade-offs.
Excellent communication skills to collaborate with BI engineers, data
engineers, and cross-functional stakeholders.
Curiosity and self-sufficiency—ability to learn new tooling quickly (Materialize,
cluster management, etc.).
Problem-solving capabilities with attention to detail and ownership of
Deliverables.
Team-oriented attitude with the ability to support both upstream and
downstream engineering partners.
Why You Will Love Working with Us
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 play a vital role in our continued success. Lean Tech is an equal opportunity
employer. We celebrate diversity and are committed to creating an inclusive
environment for all employees.
