Mid-level Data Engineer

This is a fully remote position, open to applicants in Mexico.

📋 Description

• Join a team dedicated to assisting both new and existing customers with their data engineering requirements.

• Advise customers on optimal technical choices to help them reach their objectives.

• Engage with multiple customer accounts, tracking and reporting on their progress effectively.

• Design, construct, and operationalize intricate data solutions, address issues, implement transformations, and suggest data cleansing/quality measures.

• Evaluate data sources to assess their worth and recommend their inclusion in analytical workflows.

• Apply fundamental data management skills, including data governance, data security, and data quality.

• Collaborate within and across teams to facilitate delivery and educate end users on data products and analytical environments.

• Conduct analysis, assessment, and resolution of defects and incidents of moderate complexity, correcting them as necessary.

• Test data movement, transformation code, and data components.

⛳️ Requirements

• A highly driven individual with a commitment to continuous learning.

• Exceptional time management and prioritization abilities.

• Strong verbal and written communication skills in English.

• Familiarity with public cloud services such as AWS, Azure, or GCP.

• Preferred: Experience in one or more of the following areas:

• Data Engineering technologies (e.g., Spark, Hadoop, Kafka)

• Data Science and Machine Learning technologies (e.g., pandas, scikit-learn, HPO)

• Data Warehousing (e.g., SQL, OLTP/OLAP/DSS)

• Preferred: Databricks data engineering or machine learning certification.

• Bachelor’s Degree in Computer Science or a related Engineering field.

🏝️ Benefits

• Innovative Environment: Collaborate with cutting-edge technologies and industry leaders in data engineering and AI.

• Customer Impact: Contribute significantly to how businesses utilize data for strategic decision-making.

• Career Growth: Access to professional development opportunities and pathways for career advancement.

• Collaborative Culture: Become part of a supportive team that values teamwork and knowledge sharing.