Mid-Senior Data Engineer

at  Devengine

Mid-Senior Data Engineer
Remote - Canada | Contract
Our client is a fast-growing Snowflake Services Partner working across North America, looking for 2 (two) Mid-Senior Data Engineers as they are building a remote data engineering team in LATAM. It’s a long-term contract opportunity without the end-date. The engagement is fully remote, successful candidates can be located anywhere in Latin America, as long as you are available for a significant overlap with the PST time zone. You’ll need to have good English communication skills (at least B2+ or higher) for this role.
This is a great opportunity for data engineers interested in training, certifications, and gaining international experience and English language proficiency. We want to hear from you if you are ready to break boundaries in the data world, work with innovative clients, and love to continuously research and learn new technologies like DBT, Airbyte and Airflow, or Terraform.

REQUIREMENTS:

Passion for data and engineering excellence
5+ years of industry experience
Strong command of SQL, hands-on experience in writing complex queries, optimizing database performance, and designing efficient database schemas.
Proven skills in creating and maintaining data models, including conceptual, logical, and physical models.
Intermediate level ETL experience
Familiarity with data warehousing concepts and have hands-on experience with data warehousing solutions such as Amazon Redshift, Google BigQuery, or Snowflake (preferred)
Intermediate level hands-on experience building data solutions using a variety of traditional and/or big data technologies
Software engineering experience is an asset

Interact with internal technical teams and potentially purely business-oriented clients: analyze customer data requirements and participate in crafting suitable solutions.
Collect data from various sources, such as databases, APIs, and logs, and integrating it into a unified data ecosystem.
Perform data cleaning, structuring, and transformation tasks to ensure that raw data is in a usable format for analysis.
Manage databases, including creating and maintaining database structures, optimizing query performance, and ensuring data consistency and integrity.
Work on developing and maintaining ETL pipelines, which involve extracting data from source systems, transforming it into the desired format, and loading it into a destination database or data warehouse.
Monitor data quality, implement data validation checks, and troubleshoot data-related issues to maintain data accuracy and reliability.