Senior Data Engineer

We are seeking a seasoned data engineer to join our team at SurveyMonkey. As a Senior Data Engineer, you will be responsible for building and managing end-to-end data pipelines using modern cloud technologies. Your role will involve designing, architecting, and building data pipelines to support existing data models, ensuring data quality through quality checks, and building new data models. Additionally, you will be responsible for writing performant transformations in Snowflake, implementing ETL best practices, and translating business requirements into technical specifications. This is an opportunity to lead data engineering initiatives and contribute to the central data organization at SurveyMonkey.

Design, architect and build data pipelines to support existing data models

Build quality checks in the end-to-end data pipelines

Build new Data models (Fact vs Dimension). Write performant/idempotent transformations in Snowflake

Build data pipeline using Python scripting (in a modular/loop context). Write well-tested, production-ready code in Python and Snowflake SQL

Hands-on experience implementing ETL (or ELT) best practices

Translate business requirements to technical specifications, form project scope, and deliver deployable code

Write complex data engineering Snowflake - SQL jobs that perform sophisticated queries on the entirety of our datasets

Document our systems for internal and external stakeholders

Monitor and debug data pipelines running on Airflow

Participate in code reviews

Mentor data engineers on best practices and coding standards

• 7+ years experience in data engineering and Data warehousing technologies
• 3+ years experience in Snowflake/ETL or similar technologies like Redshift
• Understanding of digital marketing and systems concepts, processes, and data
• Experience working extensively with Digital Marketing: Google Ads, Meta Ads, Paid Media Marketing, etc
• Experience building Data integrations with Marketing systems
• Experience with AWS cloud services: S3, EC2, RDS, Spark, EMR etc
• Experience with object-oriented/object function scripting languages: Python (preferred), Java, Scala, etc.
• Experience in orchestrating, automating, and deploying production data pipelines using Airflow/Luigi, etc
• Experience with DevOPS: Git, Github actions, CI/CD pipelines, Terraform, etc
• Experience with tools such as DBT or other similar technologies
• Experience with transforming, and developing data structures, metadata, dependency, and data workflows to support an Analytics function
• In-depth knowledge of Data lakes, EDW concepts, and data modeling (Star, Snowflake, and Galaxy schemas)

• Competitive base pay ranging from $126,560/year to $189,840/year
• Bonuses and commissions may be offered as part of the total compensation package
• Medical, dental, vision, life, and disability insurance
• 401(k) retirement plan
• Flexible spending and health savings account
• Paid holidays
• Paid time off
• Employee assistance program
• Inclusive workplace promoting diversity and equal opportunity
• Curiosity-driven and innovative culture
• Choice Model allowing employees to choose their preferred work arrangement (in-person, fully remote, or hybrid)
• Commitment to creating forward-looking benefits policies and employee programs
• Annual holiday refresh and week of service
• C.H.O.I.C.E Fund for employee support
• Accommodations available for applicants with disabilities