Build and maintain scalable data pipelines and infrastructure using Snowflake, AWS Glue, and modern ETL/ELT frameworks.
Integrate data from platforms such as Salesforce, Mixpanel, Segment, Customer.io, Intercom, Google Analytics, and LinkedIn Ads.
Develop reliable data models, warehouses, and data lakes to support reporting and analytics.
Implement data quality, monitoring, governance, and security best practices.
Build AI-powered self-service analytics capabilities for business users.
Partner with Revenue Operations, Product, Marketing and BI teams to deliver impactful data solutions.
Optimize platform performance, reliability, and cost efficiency.

3+ years of Data Engineering experience.
Strong expertise in Snowflake, including architecture, performance optimization, governance, and security.
Experience with AWS Glue (PySpark), ETL/ELT pipelines, and workflow orchestration.
Advanced SQL and Python skills.
Experience with PostgreSQL, MongoDB, Amazon S3, and modern cloud data architectures.
Strong understanding of data modelling, warehousing, and analytics engineering practices.
Experience integrating SaaS platforms and revenue data across customer, product, and marketing functions.
Knowledge of data governance, privacy, and compliance frameworks such as GDPR.
Strong problem-solving skills, ownership mindset, and attention to detail.

Data Engineer

Key skills