Data Engineer

Join Hire Hangar and work with fast-growing global companies while building a long-term, remote career.Job Title Data Engineer – Tech IndustryLocation RemoteTime 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 ResponsibilitiesDesign, build, and maintain robust, scalable data pipelines and ETL/ELT workflowsDevelop and manage data warehousing solutions to support business intelligence and analytics needsEnsure data quality, integrity, and availability across all data systems and sourcesCollaborate with data scientists, analysts, and product teams to understand and fulfill data requirementsOptimize query performance and database architecture for speed and efficiencyMonitor, troubleshoot, and resolve data pipeline failures and incidentsImplement and enforce data governance, security, and compliance best practicesDocument data models, processes, and infrastructure to support team knowledge sharingRequired Qualifications4+ 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 ScalaHands-on experience building and managing ETL/ELT pipelines using tools such as Apache Airflow, dbt, or similarExperience with cloud data platforms such as AWS, GCP, or Azure, and data warehouses such as Snowflake, BigQuery, or RedshiftSolid understanding of data modeling, schema design, and database optimizationStrong problem-solving skills with the ability to manage complex, high-volume data environmentsMust 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 QualificationsExperience with real-time or streaming data pipelines using tools such as Kafka or SparkFamiliarity with data lakehouse architectures (e.g., Delta Lake, Apache Iceberg)Exposure to machine learning workflows and supporting ML data infrastructureExperience working in an Agile or DevOps environment with CI/CD practices applied to data workflowsTools & TechnologyPython, SQL, or ScalaApache Airflow, dbt, or equivalent pipeline orchestration toolsSnowflake, BigQuery, or RedshiftAWS, GCP, or AzureKafka or Spark (advantageous)Google WorkspaceSlack, Zoom, Jira, and other remote collaboration toolsPlease NOTEIt 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.We connect top talent with vetted employers, competitive pay, and real growth opportunities.Originally posted on Himalayas