What are the responsibilities and job description for the Data Engineer (Airflow, Python, AWS, DBT, Snowflake) position at Data Vizionaries?
Company Description
Data Vizionaries is a forward-thinking organization dedicated to turning complex data into actionable insights. The company leverages cutting-edge technology to create innovative data solutions, enabling businesses to make informed decisions. With a focus on collaboration and excellence, Data Vizionaries is committed to fostering a culture of growth and creativity for its team members. Our mission is to empower clients with tools and strategies to extract value from their data, driving business success.
Role Description - Onsite Jacksonville, FL
We are seeking a Data Engineer to design, build, and optimize high-performance data workflows that fuel our analytical and operational ecosystems. In this capacity, you will take ownership of the full data lifecycle—orchestrating seamless ingestion and executing complex transformations utilizing Python, AWS, DBT, and Snowflake, while managing scheduling and workflows via Airflow and Astronomer. Your primary focus will be delivering highly dependable, well-governed, and easily accessible data architectures across the entire enterprise. Acting as a critical technical bridge, you will collaborate closely with engineering teams and corporate business leaders to deploy scalable, meticulously documented solutions that drive intelligent automation and strategic insights.
Qualifications
- 2 years of dedicated data engineering experience, with a proven track record of launching and expanding contemporary analytical platforms.
- Orchestration Expertise: Deep operational knowledge of workflow management using Airflow, specifically within managed Astronomer environments.
- Mastery of Python scripting and sophisticated SQL programming to drive automation, data manipulation, and pipeline tuning.
- Deep, hands-on experience with Snowflake data warehouses, dbt compilation, and workflow schedulers like Airflow.
- Direct experience working with AWS services, Fivetran connectors, and Docker containers.
- Comprehensive understanding of data warehousing methodologies, schema design, and CI/CD deployment automation.
- Diverse Data Handling: Proficiency in processing and ingesting varied data types, including JSON, Parquet, and Avro formats.
- Infrastructure Skills: Familiarity with containerized applications and infrastructure-as-code principles.