Senior Data Engineer

Simple Life App; Spain (TX); Hybrid; USD 130,000 - 185,000; Full time

Benefits offered by this job

Stock options

Hybrid work opportunities

Competitive salary package

21 days annual leave

Job summary

Simple Life is seeking a Senior Data Engineer to join our Tech team. You will design and maintain streaming pipelines, build ingestion from APIs, and migrate existing pipelines to our in-house infra.

You will work with Snowflake, Terraform, and AWS components, ensuring data quality and resilient data flows for AI tooling. The role offers in-office, remote, and hybrid options, a competitive salary, stock options, and 21 days of annual leave.

Qualifications

• 5+ years of Python experience in backend or data engineering roles.
• Strong understanding of distributed systems architecture and trade-offs of sync vs async processing.
• Hands-on experience with AWS services (Lambda, API Gateway, containers in ECS/EKS).
• Experience building streaming pipelines (Kinesis, SQS, or equivalents).
• Experience with infrastructure as code (Terraform or equivalents).
• Working knowledge of SQL including joins and window functions.
• Experience handling messy, duplicated, delayed, or malformed production data.
• Understanding of data flow in production systems and preventing downstream issues.
• Operational mindset: owning production systems and monitoring them.

Responsibilities

• Design, build, and maintain streaming pipelines.
• Develop ingestion pipelines from third-party APIs, webhooks, and SDKs.
• Migrate data ingestion pipelines from SaaS tools to in-house infrastructure.
• Deliver data to Snowflake raw layer with schema consistency and resilience.
• Evolve the AWS streaming stack (Kinesis, SQS, Lambda, API Gateway) for cost efficiency and reliability.
• Maintain infrastructure as code (Terraform) for ingestion and processing resources.
• Monitor pipelines, troubleshoot, and resolve incidents.
• Contribute to safe data access for AI agents and tooling.
• Continuously improve ingestion architecture and practices.

Skills

Python

Distributed systems

AWS

Streaming pipelines

Terraform

SQL

Production data

Data flow

Architecture decisions

Observability

Tools

Snowflake

dbt

Airflow

Dagster

Job description

Simple Life is the #1 AI-powered health coaching app for adults who want to lose weight and enjoy a healthier lifestyle—without the stress or extremes. Our mission is to empower people to feel their best every day. By challenging traditional, restrictive approaches, Simple offers a more sustainable method grounded in ease, personalization, and real-life support.

Simple has had over 17 million downloads and more than 300,000 5-star reviews, having helped millions lose weight successfully and sustainably. Simple has earned recognition as Best Virtual Coach and one of the Top 100 AI companies — all thanks to a dedicated global team driving real impact.

With SIMPLE as a partner in their pocket, users feel cared for and empowered to embrace — and stick to — new healthy habits. To learn more, visit simple.life.

Simple is looking for a Senior Data Engineer to join our Tech team.

Push the pace of innovation and build a future of a healthier world with us!

Key Responsibilities

• Design, build, and maintain streaming pipelines.
• Develop custom ingestion pipelines from third-party APIs, webhooks, and SDKs.
• Migrate existing data ingestion pipelines from SaaS tools to our own infrastructure.
• Deliver data to the raw layer of our Snowflake warehouse with schema consistency, idempotency, and resilience to malformed or late data.
• Evolve the existing AWS streaming stack (Kinesis, SQS, Lambda, API Gateway), improving cost efficiency, observability, and resilience.
• Maintain infrastructure as code (Terraform) for ingestion and processing resources.
• Monitor pipelines, troubleshoot, and resolve incidents.
• Contribute to our ongoing work on safe data access for AI agents and tooling.
• Continuously improve ingestion architecture, tooling, and engineering practices.

What We’re Looking For

• 5+ years of commercial Python experience in a backend or data engineering role.
• Solid understanding of distributed systems architecture, including load balancing, sharding, and trade-offs between synchronous and asynchronous processing.
• Hands‑on experience with cloud services, preferably AWS (Lambda, API Gateway, containers in ECS/EKS).
• Experience building streaming pipelines (Kinesis, SQS, or equivalents).
• Experience with infrastructure as code (Terraform or equivalents).
• Working knowledge of SQL: ability to read and write queries, including joins and window functions.
• Commercial experience with real-world production data: ability to design systems that gracefully handle messy, duplicated, delayed, or malformed input.
• Solid understanding of how data flows through production systems, including the ability to anticipate and prevent downstream issues.
• Operational mindset: comfortable owning production systems and monitoring them.
• Ability to make architectural decisions independently and review the work of teammates.

Nice to Have

• Strong SQL and data modeling skills.
• Experience with Snowflake and dbt.
• Experience with workflow orchestrators (Airflow, Dagster, Prefect, or equivalents).
• Experience working with analytics and product teams as a data provider.
• Experience working with sensitive or regulated data.

Perks And Benefits

• Open-minded teams, a welcoming and inclusive company culture, plus the opportunity to make a real difference with a game-changing health tech product.
• A competitive salary package based on your unique expertise, skillset, and impact on the product plus stock options.
• In-office, remote and hybrid work opportunities.
• The equipment whatever you need to be happy and productive.
• A premium SIMPLE subscription.
• 21 days annual leave, plus bank holidays (those observed where you live).
• Flexible hours. We focus on your results, not how long you spend at your desk.

About Our Values

• Think deeper: We understand that in order to grow we need to make all our decisions reality-based and change our opinion based on what we learn. We appreciate data coming in various forms – quantitative and qualitative, feedback from users and colleagues, and strong and weak signals.We treat data as the main source for leveraging insights and expect people at every level to have conversations that start with data.
• Focus on impact: Results and speed matter. When we are competing to become an A-player in the digital health market, we don’t have the luxury of deliberation. We need to make decisions and changes quickly and, swiftly learn from our mistakes.We prioritize what will have the greatest impact and aren’t distracted by anything else. We create products that benefit users while we are meeting our metrics.
• Take ownership: We seek to improve all facets of our company even in ways beyond our job description. We seek and take responsibility for our actions and their impact. We value and set high expectations for our own work so that it can add to the overall quality and innovation results of the team. Each one of us is empowered to make this company a success, take the lead to resolve disagreements and systemic issues.
• Push the limits: We encourage our team to explore new ideas, challenge conventional thinking, and continuously improve work. This mindset can lead to breakthroughs in product development, improved operational efficiency, and increased competitiveness in the market. We believe that a culture and mindset of constantly striving to exceed existing standards, boundaries, or expectations that include innovation, experimentation, and a willingness to take risks, can bring us success. We don't accept what someone says as truth if we disagree with it, no matter what authority that person has in the company and express ourselves directly, not through back channels. We challenge ideas, from policy to product decisions, and always seek to understand the reason behind what we do.
• Be a Championship Team: As a part of the championship team, you must improve your own performance constantly also know your teammates, their talents and skills and be focused on a common goal and how to achieve it together. We hold each other accountable for our contribution to the shared success or failure, and we constantly look for ways to help our colleagues to improve and for us to perform better as a team. We collaborate within the team in order to compete with challengers in the outside world. We build relationships of trust. We provide our teammates with the autonomy and support they need to deliver their part of the goal.