Hatch
Data Engineer
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About Hatch At Hatch, we’re building AI that doesn’t just assist behind the scenes; it converses with customers out in the wild. Backed by Y Combinator and top-tier investors like Bessemer and NextView, we’re scaling fast, doubling revenue year over year, and looking for A players to help us cement our place as the category leader in AI for customer engagement.
Company website : https://www.usehatchapp.com/
MUST BE BASED IN NYC - No Relocation
Cannot Sponsor
About the Role We are looking for a skilled Data Engineer with strong full-stack/back-end engineering experience to join our growing data team. You will be responsible for building, optimizing, and maintaining data pipelines and platform services that power our analytics, reporting, and AI initiatives.
Our data volume and the sophistication of our AI models are growing rapidly. To keep pace, we need engineers who treat data systems as production software, not just analytics plumbing. If you love writing robust code, designing for scale, and operating distributed systems in production, let’s talk.
Note: This is not a business‑intelligence or analyst role. Candidates whose primary experience is building reports or dashboards will not be successful here.
Key Responsibilities
Design, build, and own scalable batch and real-time data pipelines using technologies such as Kinesis, Pub/Sub, Flink, Spark, Airflow, and dbt.
Develop and maintain well‑designed APIs, SDKs, and backend services that integrate seamlessly with data infrastructure.
Apply software engineering best practices—modular design, testing, CI/CD, observability, and code reviews to all data and service development.
Model, partition, and optimize datasets in data lakes and warehouses (BigQuery, Aurora PostgreSQL) with attention to performance, cost, and governance.
Collaborate with backend and platform engineers to define data contracts, streaming interfaces, and shared service boundaries.
Drive infrastructure‑as‑code and container orchestration (Terraform, Docker, Kubernetes/EKS) for data and service deployment.
Establish and monitor SLOs for data quality, latency, and availability; investigate and resolve production issues across the stack.
Contribute to architectural discussions, ensuring designs follow scalable patterns such as event‑driven, microservice, and domain‑driven architectures.
What We're Looking For
5+ years combined experience in backend/full‑stack and data engineering, including 3+ years building production services in Python or Go.
Proven ability to design and implement clean, maintainable, and performant APIs and systems following modern software patterns (e.g., layered architecture, dependency injection, repository pattern).
Strong understanding of computer‑science fundamentals—data structures, algorithms, concurrency, networking, and distributed systems.
Expertise with distributed data technologies: Kafka/Kinesis/PubSub, Spark/Flink/Dask, Redis, MongoDB, BigQuery.
Hands‑on experience instrumenting, monitoring, and troubleshooting services in AWS and GCP (CloudWatch, Prometheus/Grafana).
Strong SQL skills and practical knowledge of dimensional, event‑driven, and domain data modeling.
Familiarity with containerization, CI/CD pipelines, and deployment strategies (Kubernetes/EKS, Terraform, blue‑green or canary).
Comfortable working across multiple cloud platforms (AWS and GCP).
Excellent written and verbal communication—you can explain complex systems clearly and advocate for sound engineering decisions.
Nice to Have
Experience supporting ML and LLM inference pipelines in production (vector databases, feature stores, prompt orchestration).
Exposure to event‑driven microservices, schema governance (protobuf/Avro), and schema registry management.
Prior success in a fast‑moving startup environment where you contributed to both application and data systems.
What We Offer
Competitive salary and equity
Remote (Eastern or Central Time Zone required) OR Hybrid work environment (3 days/week in our NYC office)
Medical, dental, and vision benefits
401(k) plan
Flexible PTO
Opportunity to build at the ground floor of a high‑growth, mission‑driven company
Not offering sponsorship
Why Hatch
Shape the future of AI‑driven customer service
Build alongside founders and leaders who value speed, ownership, and ambition
Solve hard problems that impact real businesses and customers
Join a team of builders who care about great engineering, fast execution, and each other
#J-18808-Ljbffr
About Hatch At Hatch, we’re building AI that doesn’t just assist behind the scenes; it converses with customers out in the wild. Backed by Y Combinator and top-tier investors like Bessemer and NextView, we’re scaling fast, doubling revenue year over year, and looking for A players to help us cement our place as the category leader in AI for customer engagement.
Company website : https://www.usehatchapp.com/
MUST BE BASED IN NYC - No Relocation
Cannot Sponsor
About the Role We are looking for a skilled Data Engineer with strong full-stack/back-end engineering experience to join our growing data team. You will be responsible for building, optimizing, and maintaining data pipelines and platform services that power our analytics, reporting, and AI initiatives.
Our data volume and the sophistication of our AI models are growing rapidly. To keep pace, we need engineers who treat data systems as production software, not just analytics plumbing. If you love writing robust code, designing for scale, and operating distributed systems in production, let’s talk.
Note: This is not a business‑intelligence or analyst role. Candidates whose primary experience is building reports or dashboards will not be successful here.
Key Responsibilities
Design, build, and own scalable batch and real-time data pipelines using technologies such as Kinesis, Pub/Sub, Flink, Spark, Airflow, and dbt.
Develop and maintain well‑designed APIs, SDKs, and backend services that integrate seamlessly with data infrastructure.
Apply software engineering best practices—modular design, testing, CI/CD, observability, and code reviews to all data and service development.
Model, partition, and optimize datasets in data lakes and warehouses (BigQuery, Aurora PostgreSQL) with attention to performance, cost, and governance.
Collaborate with backend and platform engineers to define data contracts, streaming interfaces, and shared service boundaries.
Drive infrastructure‑as‑code and container orchestration (Terraform, Docker, Kubernetes/EKS) for data and service deployment.
Establish and monitor SLOs for data quality, latency, and availability; investigate and resolve production issues across the stack.
Contribute to architectural discussions, ensuring designs follow scalable patterns such as event‑driven, microservice, and domain‑driven architectures.
What We're Looking For
5+ years combined experience in backend/full‑stack and data engineering, including 3+ years building production services in Python or Go.
Proven ability to design and implement clean, maintainable, and performant APIs and systems following modern software patterns (e.g., layered architecture, dependency injection, repository pattern).
Strong understanding of computer‑science fundamentals—data structures, algorithms, concurrency, networking, and distributed systems.
Expertise with distributed data technologies: Kafka/Kinesis/PubSub, Spark/Flink/Dask, Redis, MongoDB, BigQuery.
Hands‑on experience instrumenting, monitoring, and troubleshooting services in AWS and GCP (CloudWatch, Prometheus/Grafana).
Strong SQL skills and practical knowledge of dimensional, event‑driven, and domain data modeling.
Familiarity with containerization, CI/CD pipelines, and deployment strategies (Kubernetes/EKS, Terraform, blue‑green or canary).
Comfortable working across multiple cloud platforms (AWS and GCP).
Excellent written and verbal communication—you can explain complex systems clearly and advocate for sound engineering decisions.
Nice to Have
Experience supporting ML and LLM inference pipelines in production (vector databases, feature stores, prompt orchestration).
Exposure to event‑driven microservices, schema governance (protobuf/Avro), and schema registry management.
Prior success in a fast‑moving startup environment where you contributed to both application and data systems.
What We Offer
Competitive salary and equity
Remote (Eastern or Central Time Zone required) OR Hybrid work environment (3 days/week in our NYC office)
Medical, dental, and vision benefits
401(k) plan
Flexible PTO
Opportunity to build at the ground floor of a high‑growth, mission‑driven company
Not offering sponsorship
Why Hatch
Shape the future of AI‑driven customer service
Build alongside founders and leaders who value speed, ownership, and ambition
Solve hard problems that impact real businesses and customers
Join a team of builders who care about great engineering, fast execution, and each other
#J-18808-Ljbffr