Senior Data Engineer
$160,000-$200,000
Apply (opens in a new tab)Senior Data Engineer
Posted 2 days ago
SENIORITY
Lead
SALARY
$160,000-$200,000
About the role
- At SimplePractice, culture is our foundation. It influences the way we work, how we serve our customers, and how we approach accomplishing our mission. We have five core values that we strive to embody every day: We think big
- We take simplicity seriously
- We come as we are
- We act with humility
- We are built on trust
- Partner with Product, Analytics and Engineering to build scalable systems that help unlock the value of data from a wide range of sources such as backend databases, event streams, and marketing platforms
- Lead technical vision and architecture with holistic point of view on both short-term and long-term horizons
- Work with analytics to create company wide alignment through standardized metrics across the company
- Work with Product and Engineering teams to support internal use cases such as financial reporting, product analytics and operational metrics
- Enable external use cases like customer-facing dashboard, self-serve analytics, and next best action in product
- Manage the complete data stack from ingestion through data consumption
- Build tools to increase transparency in reporting company wide business outcomes
- Work with DevOps to deploy and maintain data solutions leveraging cloud data technologies, preferably in AWS
- Help define data quality and data security framework to measure and monitor data quality across the enterprise. Define and promote data engineering best practice
- BS/MS in Engineering, Computer Science, Mathematics, or related field
- 7+ years in Data or Analytics Engineering
- Strong problem-solving and communication skills; comfortable in fast-paced, cross-functional environments
- Data Engineering & Pipelines
- Enterprise architecture and enterprise data architecture (data modeling and enterprise dimensional modeling)
- Expert in SQL and data modeling (relational, dimensional, semantic)
- Proven experience in data warehouse design, implementation, and maintenance (Snowflake)
- Hands-on with DBT for modular, testable transformations
- Experience with orchestration and ingestion tools: Airflow, Prefect, Airbyte, Fivetran, Kafka
- Familiar with ELT, schema-on-read, DAGs, and performance optimization
- Cloud & Infrastructure
- Experience with AWS (S3, RDS, Redshift, etc.)
- Familiar with Terraform, Docker, and containerized workflows (bonus)
- Skilled in handling structured, semi-structured (e.g., JSON), and columnar formats (e.g., Parquet, ORC)
- Analytics & Enablement
- Experience building and supporting semantic layers for self-serve analytics
- Proficient with BI tools like Looker, Tableau, or Sisense
- Comfortable standardizing metrics and enabling trusted, consistent access to data
- Programming & Scripting
- Proficient in Python and Unix/Linux scripting
- Comfortable working with APIs (e.g., using curl)
- AWS DevOps - Terraform, Kubernetes, Docker
- Project & Change Management skills especially experience working in an Agile (SCRUM, Kanban) environment/team focusing on sprint by sprint deliveries
- Real-time ETL - Kafka streaming, AWS Kinesis
- We offer a competitive benefits program including: Medical, dental, vision, life & disability insurance
- 401(k) plan with company match
- Flexible Time Off (FTO), wellbeing days, paid holidays, and summer Fridays
- Mental health resources
- Paid parental leave & Backup Care
- Tuition reimbursement
- Employee Resource Groups (ERGs)
Before you apply
Applying takes about a minute. These four things decide how fast it moves after that.
Your profile is current
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Two examples you can talk through
Not a portfolio — just two pieces of work where you can explain the decisions and what you'd change.
A number in mind
What you're on now and what would make you move. We negotiate better when we know both.
Your notice period
Employers plan around it, and it's the question that stalls offers most often.
Once you apply, someone reads it and calls you before anything reaches the employer — usually within two working days.
