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Senior/Lead Data Orchestration Engineer ID22338

Remote: 
Full Remote
Contract: 
Experience: 
Mid-level (2-5 years)
Work from: 

Offer summary

Qualifications:

4+ years of experience as a Data Engineer, Proficient in Python and SQL, Experience with Airflow and Dagster, Knowledge of Snowflake and Databricks, Upper-intermediate English level.

Key responsabilities:

  • Design clear data models and transformations
  • Validate data and conduct model testing
  • Build data products for knowledge discovery
  • Oversee maintenance of data pipelines
  • Collaborate on robust data warehouse architecture
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Agile Engine Computer Software / SaaS Large https://join.agileengine.com/
1001 - 5000 Employees
See more Agile Engine offers

Job description

What you will do

  • Design a clear and lean data model that clearly outlines data sources and transformations over this data on top of DAGs and data orchestration tools like dagsters or airflow;
  • Data validation and data model testing on each DAG step;
  • Insights Layer Ownership: Build data models and algorithms to generate first-party data using statistical and machine learning techniques, including LLMs and natural language processing. Generate derived insights and determine accurate values from error-prone sources (e.g., headcount information);
  • Data Product Development: Develop and enhance data products to improve the discoverability of meaningful knowledge and information in our database. Continuously improve similarity, relevance, normalization, and tagging algorithms that power our search engine;
  • Pipeline Maintenance: Oversee data pipelines’ maintenance and health to ensure accurate, efficient, and optimal data transformations by avoiding repetitive tasks or operations within the data;
  • Team Collaboration: Collaborate with the team to devise product goals, outline milestones, and execute plans with minimal guidance;
  • Data Warehouse Design: Contribute to the design of a robust data warehouse architecture by following best practices and industry standards. Transferring data from S3, loading data with different schedules and managing different data pipelines on top of a unique warehouse architecture, etc;
  • Collaborate with our platform team to make design decisions on the optimal middle-layer database flow improving DAG execution times and costs.


Must haves

  • +4 years of experience as a Data Engineer;
  • Programming Languages: Python, SQL;
  • Orchestration Tools: Airflow, Dagster;
  • Data Warehouses: Snowflake, Databricks;
  • ETL Tools: DBT Models;
  • Containerization: Docker;
  • DevOps: AWS;
  • Databases: Clickhouse, Postgres, DuckDB;
  • Upper-intermediate English level.


The benefits of joining us

  • Professional growth

Accelerate your professional journey with mentorship, TechTalks, and personalized growth roadmaps


  • Competitive compensation

We match your ever-growing skills, talent, and contributions with competitive USD-based compensation and budgets for education, fitness, and team activities


  • A selection of exciting projects

Join projects with modern solutions development and top-tier clients that include Fortune 500 enterprises and leading product brands


  • Flextime

Tailor your schedule for an optimal work-life balance, by having the options of working from home and going to the office, whatever makes you the happiest and most productive

Required profile

Experience

Level of experience: Mid-level (2-5 years)
Industry :
Computer Software / SaaS
Spoken language(s):
EnglishEnglish
Check out the description to know which languages are mandatory.

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