Intermediate Data Engineer

What You Do

As an Intermediate Data Engineer, you will support the development and maintenance of data pipelines, ingestion processes, and data transformations. You'll create and maintain SQL queries, Python scripts, and Spark-based workloads for data processing and analytics.

• Support development and maintenance of data pipelines, ingestion processes, and data transformations
• Create and maintain SQL queries, Python scripts, and Spark-based workloads
• Troubleshoot pipeline failures, data quality issues, and operational incidents
• Work with senior engineers on schema mappings, transformation logic, and data validation rules
• Ensure datasets meet expected schemas, data contracts, and quality standards
• Support metadata management, dataset documentation, and lineage activities
• Maintain data classification according to company standards
• Automate repetitive operational and data management tasks
• Contribute to monitoring, alerting, and operational support for data pipelines
• Participate in testing including unit tests, transformation validation, and data quality checks
• Follow established engineering standards, coding practices, and team development patterns
• Apply security, privacy, and compliance requirements for sensitive or regulated data
• Collaborate with Data Governance, Security, and Compliance teams as needed
• Contribute to continuous improvement initiatives focused on data trust and reliability

Requirements and Qualifications

• Bachelor's degree in Computer Science, Computer Engineering, Information Systems, Data Science, Software Engineering, or related field
• Up to 2 years of experience in Data Engineering, Software Engineering, Data Analytics, or related areas
• Knowledge of SQL and Python
• Understanding of ETL/ELT concepts and data transformation processes
• Familiarity with relational databases and data warehousing concepts
• Basic knowledge of Spark, Databricks, or distributed data processing frameworks
• Familiarity with Git and version control workflows
• Basic understanding of cloud platforms such as AWS, Azure, or Google Cloud
• Knowledge of automation concepts and scripting for operational efficiency
• Basic understanding of data quality concepts and validation practices
• Familiarity with data governance principles including metadata, ownership, and documentation
• Basic knowledge of data classification concepts
• Understanding of data lineage and traceability concepts
• Awareness of security best practices including access management and least-privilege principles
• Strong analytical, problem-solving, and communication skills
• Basic to intermediate English

Salary Disclosure: This position's estimated salary range of $130,000–$185,000 USD annually is an editorial market estimate based on role level, location, and industry benchmarks. It is not employer-provided compensation information and may vary significantly based on individual experience, qualifications, location, and market conditions. Please contact the employer directly for official compensation details.