Lead Data Orchestration Engineer Id22338

Detalles de la oferta

Job Description

This is a remote position and we are hiring candidates from the whole country.

AgileEngine is one of the Inc. 5000 fastest-growing companies in the US and a top-3 ranked dev shop according to Clutch.

We create award-winning custom software solutions that help companies across 15+ industries change the lives of millions.

If you like a challenging environment where you're working with the best and are encouraged to learn and experiment every day, there's no better place - guaranteed! : )

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 Dagster 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; 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.

Requirements 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.
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Fuente: Jobrapido_Ppc

Requisitos

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