As a Data Engineer within an innovative SaaS company, you will design, build, and maintain scalable data infrastructure that powers product analytics and data-driven decision-making.
Build and optimize ETL/ELT workflows for large-scale structured and unstructured application, customer, product, and operational datasets.
• Integrate and manage data from multiple sources, including SaaS applications, product databases, customer platforms, APIs, third-party services, and internal systems.
• Ensure data quality, consistency, and reliability across data platforms through validation, monitoring, testing, and governance processes.
• Develop scalable data models, warehouse structures, and semantic layers to support analytics, reporting, experimentation, and machine learning initiatives.
• Support both real-time and batch data processing pipelines using modern data engineering tools and cloud-native technologies.
• Design and maintain data infrastructure that enables self-service analytics and efficient data consumption across technical and business teams.
• Contribute to cloud-based data architecture and platform development using AWS, Azure, or GCP.
2–5+ years of experience in Data Engineering, Analytics Engineering, Data Platform Engineering, or a related field.
• Strong programming skills in Python and/or Scala/Java for data processing and automation.
• Solid experience with SQL and designing scalable, high-performance data models.
• Hands-on experience building ETL/ELT pipelines and working with large-scale datasets in cloud environments.
• Experience with modern data warehousing solutions such as Snowflake, BigQuery, Redshift, or Databricks.
• Familiarity with cloud platforms such as AWS, Azure, or GCP.
• Experience with tools such as Airflow, Spark, Kafka, dbt, Databricks, or similar technologies is a strong advantage.
• Understanding of SaaS business models, product analytics, customer data, subscription metrics, or application telemetry is highly beneficial.
• Experience supporting data-driven product development and analytics initiatives is considered a plus.
Opportunity to contribute to a modern, data-driven SaaS platform serving a growing customer base.
• Strong emphasis on technical development, modern data architecture, and scalable cloud-native systems.
• Clear pathways for progression into Senior Data Engineer, Data Architect, Staff Engineer, or Engineering Leadership positions.
• Collaborative and high-performing team focused on building innovative software solutions through data.