Senior Data Engineer

Local or 100% Remote

Who we are 

Our mission at Point is to make homeownership more valuable and accessible to all. Every day, we explore, build, and iterate to create innovative financial products that improve the lives of our customers. Together, we’re creating the premier full-stack home equity platform to help current homeowners access their home wealth and aspiring ones realize their dream of homeownership. Point has raised over $180M from Andreessen Horowitz, WestCap, Prudential and other leading investors.

About the role

We are looking for a Senior Data Analytics Engineer to enhance and expand our data systems by maintaining and improving our analytics tools, integrating external data sources, and building reliable data sets to support reporting and business insights. This role will also focus on providing automation and tools to support data science and machine learning initiatives.

Our culture

We are a people-first, value-driven team. We come from varied backgrounds, experiences, and time zones. Our teams are aligned in service to our goal — to improve the lives of customers. Our culture is built on sharing ideas, supporting each other, and being empowered to do our best work. Find out what you can accomplish as part of an engaged, high-achieving team focused on a common goal.

Your responsibilities

• Create and maintain Apache Airflow data pipeline jobs.
• Monitor and update Fivetran extract and load runs.
• Create and govern dbt models, testing, and job runs.
• Monitor and maintain data quality processes and procedures.
• Own, manage, and govern Snowflake data warehouse, including permission grants.
• Maintain and govern usage of data sent from Snowflake to source systems (“Reverse ETL”).
• Collaborate with stakeholders to maintain and monitor existing data pipelines. 
• Evaluate automation opportunities within the business, using available data tools.
• Provide data set and tooling recommendations where appropriate.
• Provision data sets for analytic, master data, and reporting use cases.

About you

• 3-5 years of experience in data engineering, data analytics, or business analysis roles.
• 3 years of experience writing SQL for data warehousing.
• 2-3 years of experience working on data warehouses to support analytics.
• 2-3 years of experience building and maintaining enterprise data models, such as fact/dimensional star schemas.
• Proficiency in cloud data warehouses (Redshift, BigQuery, Snowflake).
• Strong SQL query writing and data modeling capabilities.
• Experience with Python for scripting, data manipulation, and API interaction.
• Familiarity with version control systems (e.g., Git, GitHub, GitLab).
• Experience with workflow orchestration tools (e.g., Apache Airflow).
• Knowledge of cloud platforms, particularly AWS.
• Experience with dbt for data transformation is preferred.
• Familiarity with BI and visualization tools (e.g., Tableau, Looker).
• Knowledge of data quality tools preferred (e.g., Monte Carlo, Metaplane, Great Expectations).
• Project management or cloud platform certifications.
• Understanding of stream processing, message queues, NoSQL databases, or Apache Spark.

Our benefits 

Generous health benefits

• We provide medical, dental, and vision plans with options for flexible spending accounts (FSA) and health savings accounts (HSA).

Unlimited paid time off

• Recharge with unlimited paid time off and 10 company holidays. 

Flexible remote & onsite work

• Our teams work from many different locations and time zones. We support fully remote work and also have an amazing in-person environment in our downtown Palo Alto, CA HQ. 

Fully paid parental leave

• Point will true-up wages from state-applicable PFL earnings so that the employee’s total gross pay will be equivalent to 100% of their regular base pay, as well as two weeks of fully paid leave to be available after exhaustion of state PFL. 
• For employees in states without Paid Family Leave, Point will provide up to 8 weeks of paid parental leave. 
• In addition, all employees will receive 4 weeks of fully paid transition time. For four weeks after returning from parental leave, and following the use of all other paid leave benefits, you may work part-time, meaning two or three days per week, and receive 100% of regular base pay.

Financial wellness

• We provide 401K retirement plans for employees as well as guaranteed life insurance and short- and long-term disability coverage. Full-time employees have the opportunity to take ownership in the company through equity options.

Extra work/life benefits

• We provide monthly stipends for internet, mobile plans, and a one-time home office reimbursement. 

Point is proud to be an equal-opportunity employer. We provide employment opportunities regardless of age, race, color, ancestry, national origin, religion, disability, sex, gender identity or expression, sexual orientation, veteran status, or any other protected class. Each individual at Point brings their own perspectives, work experiences, lifestyles, and cultures with them, and we believe that a more diverse team creates more innovative products, provides better services to customers, and helps us all grow and learn. 

Compensation at Point will be determined by skills, experience, and geographic location. Point has identified the expected annual base salary range for roles at this level based on market by tiers (Region | Location | Market Range):

• Tier 1 | San Francisco Bay Area, New York, Los Angeles, & Seattle | $145,400 - $196,700 
• Tier 2 | Chicago, Austin, Denver, Boston, Washington DC, San Diego | $123,300 - $166,800
• Tier 3 | All other US metro areas | $116,500 - $157,600

This does not include any other potential components of the compensation package, including equity, benefits, and perks outlined above. At the launch of each position, we benchmark compensation to the appropriate role and level utilizing competitive compensation data from various data sources as references. At the offer stage, we use the signal we received from our interviews coupled with your experience, location, and other job-related factors to determine final compensation. 

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