Senior Data Engineer

Posted 6 months agoViewed

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💎 Seniority level: Senior, 5+ years experience

📍 Location: USA, CAN, MEX

🔍 Industry: Transportation technology

🏢 Company: Fleetio

🗣️ Languages: English

⏳ Experience: 5+ years experience

🪄 Skills: AWSProject ManagementPythonSQLBusiness IntelligenceDesign PatternsKafkaSnowflakeTableauData engineeringServerlessCommunication SkillsCI/CD

Requirements:

5+ years experience working in a data engineering or data-focused software engineering role.
Experience transforming raw data into clean models using standard tools of the modern data stack.
Deep understanding of ELT and data modeling concepts.
Experience with streaming data and pipelines (Kafka or Kinesis).
Proficiency in Python with a proven track record of delivering production-ready Python applications.
Experience in designing, building, and administering modern data pipelines and data warehouses.
Experience with dbt.
Familiarity with semantic layers like Cube or MetricFlow.
Experience with Snowflake, BigQuery, or Redshift.
Knowledge of version control tools such as GitHub or GitLab.
Experience with ELT tools like Stitch or Fivetran.
Experience with orchestration tools such as Prefect or Dagster.
Knowledge of CI/CD and IaaC tooling such as GitHub Actions and Terraform.
Experience with business intelligence solutions (Metabase, Looker, Tableau, Periscope, Mode).
Familiarity with serverless cloud functions (AWS Lambda, Google Cloud Functions, etc.).
Excellent communication and project management skills with a customer service-focused mindset.

Responsibilities:

Enable and scale self-serve analytics for all Fleetio team members by modeling data and metrics via tools like dbt.
Develop data destinations, custom integrations, and maintain open source packages for customer data integration.
Maintain and develop custom data pipelines from operational source systems for both streaming and batch sources.
Work on the development of internal data infrastructure, improving data hygiene and integrity through ELT pipeline monitoring.
Architect, design, and implement core components of data platform including data observability and data science products.
Develop and maintain streaming data pipelines from various databases and sources.
Collaborate across the company to tailor data needs and ensure data is appropriately modeled and available.
Document best practices and coach others on data modeling and SQL query optimization, managing roles, permissions, and deprecated projects.

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