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Job Title Data Engineer – Tech Industry
Location Remote
Time Zone US Time Zones (EST–PST)
Role Overview We are seeking a skilled and detail-oriented Data Engineer to design, build, and maintain scalable data infrastructure for a fast-growing tech company. This is a full-time role requiring deep technical expertise in data pipelines, warehousing, and architecture. The ideal candidate is analytical, collaborative, and comfortable working across large datasets while partnering with data science, product, and engineering teams to deliver reliable, high-quality data solutions.
Key Responsibilities
Design, build, and maintain robust, scalable data pipelines and ETL/ELT workflows
Develop and manage data warehousing solutions to support business intelligence and analytics needs
Ensure data quality, integrity, and availability across all data systems and sources
Collaborate with data scientists, analysts, and product teams to understand and fulfill data requirements
Optimize query performance and database architecture for speed and efficiency
Monitor, troubleshoot, and resolve data pipeline failures and incidents
Implement and enforce data governance, security, and compliance best practices
Document data models, processes, and infrastructure to support team knowledge sharing
Required Qualifications
4+ years of experience as a Data Engineer or in a similar data infrastructure role within a tech company (non-negotiable)
Strong proficiency in SQL and at least one programming language such as Python or Scala
Hands-on experience building and managing ETL/ELT pipelines using tools such as Apache Airflow, dbt, or similar
Experience with cloud data platforms such as AWS, GCP, or Azure, and data warehouses such as Snowflake, BigQuery, or Redshift
Solid understanding of data modeling, schema design, and database optimization
Strong problem-solving skills with the ability to manage complex, high-volume data environments
Must have prior remote work experience, be fluent with remote collaboration tools and platforms (such as Slack, Zoom, Google Workspace, Asana, or similar), and have ideally worked with US or UK-based companies. Applications without this experience will not be considered.
Preferred Qualifications
Experience with real-time or streaming data pipelines using tools such as Kafka or Spark
Familiarity with data lakehouse architectures (e.g., Delta Lake, Apache Iceberg)
Exposure to machine learning workflows and supporting ML data infrastructure
Experience working in an Agile or DevOps environment with CI/CD practices applied to data workflows
Tools & Technology
Python, SQL, or Scala
Apache Airflow, dbt, or equivalent pipeline orchestration tools
Snowflake, BigQuery, or Redshift
AWS, GCP, or Azure
Kafka or Spark (advantageous)
Google Workspace
Slack, Zoom, Jira, and other remote collaboration tools
Please NOTE
It is crucial that you complete the application form in full. As part of the application process, you will be required to record a video. If your application is successful, you will receive an email confirming next steps—the video is the first step of the interview process. If you do not record a video, we will not be able to consider you for ANY open roles.
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