Senior Data Engineer
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Job Description
Data Engineer transforming raw application data using DBT, Materialize, and Snowflake at Lean Tech. Collaborating with teams for real-time data workflow optimization.
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.
Requirements:
- 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).
Benefits:
- Professional development opportunities with international customers
- Collaborative work environment
- Career path and mentorship programs that will lead to new levels
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