Senior Data Engineer

Job Description

Our Enterprise Data & Analytics (EDA) is looking for an experienced Senior Data Engineer to join our growing data engineering team. You’ll work in a collaborative Agile environment using the latest engineering best practices with involvement in all aspects of the software development lifecycle. 

You will craft and develop curated data products, applying standard architectural & data modeling practices to maintain the foundation data layer serving as a single source of truth across Zendesk  . You will be primarily developing Data Warehouse Solutions in BigQuery/Snowflake using technologies such as dbt, Airflow, Terraform.

What you get to do every single day:

• Collaborate with team members and business partners to collect business requirements, define successful analytics outcomes and design data models

• Serve as Data Model subject matter expert and data model spokesperson, demonstrated by the ability to address questions quickly and accurately

• Implement Enterprise Data Warehouse by transforming raw data into schemas and data models for various business domains using SQL & dbt

• Design, build, and maintain ELT pipelines in Enterprise Data Warehouse to ensure reliable business reporting using Airflow, Fivetran & dbt

• Optimize data warehousing processes by refining naming conventions, enhancing data modeling, and implementing best practices for data quality testing

• Build analytics solutions that provide practical insights into customer 360, finance, product, sales and other key business domains

• Build and Promote best engineering practices in areas of version control system, CI/CD, code review, pair programming

• Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery

• Work with data and analytics experts to strive for greater functionality in our data systems

What you bring to the role:

• 5+ years of data engineering experience building, working & maintaining data pipelines & ETL processes on big data environments

• 5+ years of experience in Data Modeling and Data Architecture in a production environment

• 5+ years in writing complex SQL queries

• 5+ years of experience with Cloud columnar databases (We use Snowflake)

• 2+ years of production experience working with dbt and designing and implementing Data Warehouse solutions

• Ability to work closely with data scientists, analysts, and other stakeholders to translate business requirements into technical solutions. Strong documentation skills for pipeline design and data flow diagrams.

• Intermediate experience with any of the programming language: Python, Go, Java, Scala, we primarily use Python

• Integration with 3rd party API SaaS applications like Salesforce, Zuora, etc

• Ensure data integrity and accuracy by conducting regular data audits, identifying and resolving data quality issues, and implementing data governance best practices.

• Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.

Preferred Qualifications

• Hands-on experience with Snowflake data platform, including administration, SQL scripting, and query performance tuning

• Good Knowledge in modern as well as classic Data Modeling - Kimball, Innmon, etc 

• Demonstrated experience in one or many business domains (Finance, Sales, Marketing)

• 3+ completed “production-grade” projects with dbt

• Expert knowledge in python

What does our data stack looks like:

• ELT (Snowflake, Fivetran, dbt, Airflow, Kafka, HighTouch)

• BI (Tableau, Looker)

• Infrastructure (GCP, AWS, Kubernetes, Terraform, Github Actions)

Hybrid: In this role, our hybrid experience is designed at the team level to give you a rich onsite experience packed with connection, collaborat