Data Engineer

We believe communication belongs to everyone. We exist to democratize phone service. Text Now is evolving the way the world connects, and that's because we're made up of people with curious minds who bring an optimistic yet critical lens into the work we do. We're the largest provider of free phone service in the nation. And we're just getting started.

Join us in our mission to break down barriers to communication and free the flow of conversation for people everywhere.

Text Now is looking for an experienced Data Engineer with hands‑ own the design, development, and maintenance of Text Now's data platform, enabling us to make effective data‑informed decisions. You will be part of cross‑functional efforts to build scalable and reliable frameworks that support all Text Now's business and data products. In this role, you can interact with different functional areas within the business and influence decision‑making in a fast‑growing mobile communications start‑up.

• Own Text Now's data warehouse, data pipelines, and integration points between various business systems.
• Design, develop, and support new and existing batch and real‑time data pipelines, and recommend improvements or modifications.
• Manage data models to enable AI/ML data products.
• Champion Text Now's data ecosystem by working with engineering and infrastructure teams to enable quicker access to data for insights and decision‑making.
• Communicate data modeling and architecture processes to cross‑functional teams.
• Identify, design, and implement process improvements across the data platform.

• Have 3–5 years of experience working with data warehouse/data lake and ETL architectures (e.g., databricks, iceberg), cloud data warehouses (e.g., Snowflake), and hands‑on experience in Python and SQL — preferably in companies with fast‑growing and evolving data needs.
• Have at least 2 years of experience with Airflow and Spark.
• Have developed scalable, real‑time data pipelines using Python/Scala, SQL, and distributed processing frameworks such as Spark or Flink.
• Have exposure to the AWS platform and services such as EKS, MSK, and MWAA (preferred).
• Have experience building data features using Snowflake, dbt, and Python to power real‑time AI/ML inference.
• Are respectfully candid, with the ability to initiate and drive tasks to completion.
• Are highly organized, dependable, and follow a structured work approach.

Canada (CAD): $88,900 - $127,000

US– National (USD): $107,800 -$154,000

US High‑Cost Locations (USD): NYC, CT, NJ, Seattle, Los Angeles, San Diego: $118,600 - $169,400

US San Francisco Bay Area (USD): $129,400 -$184,800

Our total rewards package goes beyond base salary. We offer a comprehensive benefits program, an annual performance‑based bonus, and equity opportunities that ensure you share in the success you help create.

We know that exceptional talent doesn’t always fit neatly into a range, so if you’re passionate about our mission and think you can make a difference, we encourage you to apply, even if your compensation expectations are outside the listed range. Final compensation will be determined based on a variety of factors, including your skills, experience, and location.

Our goal is to offer a competitive package that reflects the impact and expertise you bring to the team. Let's chat!

More about Text Now...

• Customer Obsessed (We strive to have a deep understanding of our customers)
• Do Right By Our People (We treat each other with fairness, respect, and integrity)
• Accept the Challenge (We adopt a "Yes, We Can" mindset to achieve ambitious goals)
• Act Like an Owner (We treat this company like it's our own... because it is!)
• Give a Damn! (We are deeply committed and passionate about our work and achieving results)

• Strong work life blend
• Flexible work arrangements (wfh, remote, or access to one of our office spaces)
• Employee Stock Options
• Unlimited vacation
• Competitive pay and benefits
• Parental leave
• Benefits for both physical and mental well being (wellness credit and L&D credit)
• We travel a few times a year for various team events, company wide off‑sites, and more

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