Data Engineer

About the Opportunity

A fast-growing technology firm in the Data Engineering & Cloud Analytics space, we build scalable data infrastructure for enterprises transforming raw data into actionable insights. Our team works across distributed systems, real-time pipelines, and cloud-native architectures to power analytics, dashboards, and ML workflows for global clients --- all in a fully remote, outcome-driven environment.

Role & Responsibilities

• Design, develop, and maintain scalable ETL/ELT pipelines using modern data stack tools for batch and real-time ingestion.
• Optimize data warehousing solutions (Snowflake, BigQuery, Redshift) and ensure data quality, lineage, and governance.
• Collaborate with Analytics, ML, and Product teams to translate business requirements into efficient, modular data models.
• Automate data validation, monitoring, and alerting using Python, SQL, and infrastructure-as-code tools.
• Deploy and manage data pipelines on cloud platforms (AWS, GCP, or Azure) using orchestration tools like Airflow or Prefect.
• Contribute to data architecture best practices, documentation, and team upskilling in CI/CD, observability, and security patterns.

Skills & Qualifications

Must-Have

• SQL
• Python
• Apache Airflow
• BigQuery
• Snowflake
• AWS (or GCP/Azure)
• ETL/ELT Pipelines
• Data Warehousing

Preferred

• dbt
• Spark
• Looker or Tableau

Benefits & Culture Highlights

• 100% remote with flexible working hours --- your schedule, your rhythm.
• Impact-driven culture: own your projects, ship fast, and see your work power real business outcomes.
• Continuous learning stipend + access to premium courses, certifications, and cloud credits.