Data Engineer, Snowplow

Role Overview

• Designing, developing, and maintaining data pipelines, including both batch ETL processes and real-time streaming solutions, to support our product teams.
• Implementing and managing Snowplow-based event tracking pipelines to collect, validate, and process user behavioral data in real time for analytics and product insights
• Collaborating with cross-functional teams (product managers, analysts, data scientists, etc.) to understand data needs and deliver insightful, scalable data solutions
• Replicating and generalizing successful data pipeline patterns to accelerate new pipeline development and ensure consistency and reliability across projects
• Developing reusable data processing utilities and tooling (leveraging common data-centric libraries and frameworks in Python) to streamline ETL/ELT workflows
• Optimizing database performance and ensuring high reliability of our data stores by performing query optimization, indexing, and tuning of SQL queries
• Monitoring and enhancing Snowplow pipeline performance and data quality: troubleshooting pipeline issues, optimizing event collection, and implementing improvements to maximize uptime and data accuracy
• Supporting data governance and quality initiatives to maintain data integrity, privacy compliance, and consistency across all data pipelines
• Providing technical guidance on data integration, transformation, and analytics best practices to team members and stakeholders
• Building reports and dashboards (in collaboration with BI/Analytics teams) to empower product and business teams with actionable insights from collected data
• Acting as a data solutions expert for the organization: advising and assisting product teams in selecting the right data architectures, tools, and approaches (e.g., choosing the appropriate data storage, streaming service, or analytics tool for a given need)
• Translating business and user requirements into technical specifications by working closely with product managers and engineers to ensure data solutions meet real-world needs

Requirements

• 5+ years of experience in data engineering, database development, and cloud-based data solutions (especially on AWS)
• Strong proficiency in SQL (T-SQL, PL/SQL) and experience with database technologies (e.g., Oracle, SQL Server, Snowflake/Redshift)
• Hands-on experience with ETL/ELT tools and frameworks, including modern cloud integration services (e.g., AWS Glue, Apache Airflow or Azure Data Factory) and dbt
• Experience with Snowplow or similar event data tracking pipelines, including their implementation, maintenance, and optimization for behavioral data collection and analytics
• Experience with data modeling, data integration, and data warehousing concepts
• Strong programming skills in Python (e.g., Pandas, automation scripting)
• Knowledge of data governance and data quality frameworks, as well as security best practices for data (e.g., GDPR)
• Experience working in Agile development environments

Tech Stack

• Airflow
• Amazon Redshift
• Apache
• AWS
• Azure
• Cloud
• ETL
• Oracle
• Pandas
• Python
• SQL

Benefits

• Health insurance
• Professional development opportunities
• Flexible working arrangements