Senior Data Engineer

Gravie
United States
Remote

Who this role is best for

Aimed at experienced data engineers who own streaming platforms and operate in regulated environments.

Best fit for

  • Candidates with 6+ years of hands-on streaming platform ownership and production experience
    — “6+ years building and operating production data systems, including demonstrated ownership of streaming or event-driven pipelines”
  • Individuals with a background in healthcare or compliance frameworks like HIPAA
    — “Health insurance domain knowledge, including HIPAA Protected Health Information (PHI) and compliance frameworks governing it.”
  • Candidates who are comfortable with infrastructure-as-code and AWS-native solutions
    — “AWS-native data engineering across streaming, processing, storage, and catalog services (e.g. MSK, EMR, Glue, S3, Athena), with infrastructure-as-code”

Things to consider

  • This role requires on-call and incident response responsibilities in a high-performance environment
    — “You are self-driven, calm under production pressure, and comfortable owning streaming systems in a regulated environment.”
  • Candidates must be proficient with Unix-based OS and command-line tools
    — “comfort on the command line / a Unix-based OS (we are 100% Mac+Linux at Gravie).”

How to stand out

  • Highlight experience with Kafka Connect, Flink checkpointing, and schema governance in your resume
    — “Deep, production experience with Apache Kafka (MSK preferred) - partitioning, consumer groups, idempotent semantics, Kafka Connect, and replay/backfill under load.”
  • Emphasize your work with CDC tools and open table formats like Iceberg or Delta Lake
    — “Change data capture and open table formats - CDC (e.g. Debezium) plus Iceberg or Delta Lake: schema evolution, partitioning, and table maintenance.”
  • Showcase your ability to define and enforce data standards and contracts
    — “Build and extend streaming pipelines that ingest CDC events ... and define standards to govern changes to them over time.”
  • Demonstrate your experience with observability tools like Datadog and CloudWatch
    — “debugging distributed data pipelines (consumer lag, data skew, backpressure, checkpoint failures, late/out-of-order events) with observability tooling (e.g. Datadog/CloudWatch).”
  • Include examples of agentic data consumption patterns and AI-assisted development tools
    — “AI-forward engineering mindset, with demonstrated hands-on use of AI-assisted and agentic development tools”
Pace · SteadyCollaboration · HighAutonomy · MediumDecision Impact · Team

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

  • Design and implementation of streaming platform
  • Operational ownership of streaming systems
  • Data access governance
Typical background
Data engineeringData architectureStreaming systems

Skills & requirements

Required

Apache KafkaApache FlinkAWSData EngineeringStreaming PipelinesData Quality ValidationObservability

Preferred

TableauPythonSQL

Stack & domain

Apache KafkaApache FlinkAWS CDKTerraformCI/CDJavaPythonSQLCommunicationProblem SolvingData EngineeringStreaming Systems

About the role

Original posting from Gravie via Ashby

Hi, we’re Gravie. Our mission is to create health benefits that actually benefit small and midsize businesses and their employees. Our innovative benefit solutions and services are developed and delivered by a diverse group of unique people. We encourage you to be your authentic self - we like you that way.

We’re building a near real-time streaming data platform on Kafka and Flink that turns operational data from across the business into canonical, contract-validated models, serving both operational applications and agentic workloads. We seek a Senior Data Engineer to build, extend, and operate it, owning the platform in production against its latency and throughput SLOs. This is a hands-on role with meaningful ownership of a live production platform.

You are self-driven, calm under production pressure, and comfortable owning streaming systems in a regulated environment.

You Will:

Share full-lifecycle ownership of the streaming platform - architecture, implementation, production operations.

  • Run the platform in production: own latency/throughput SLOs, monitoring and alerting (e.g. Datadog) - including replays, per-source backfills, connector-failure recovery, Flink checkpoint/savepoint recovery, dead-letter triage, and tuning for spiky load from batch-driven upstream sources.
  • Build and extend streaming pipelines that ingest CDC events from OLTP databases and SaaS sources into canonical, contract-validated form, and define standards to govern changes to them over time.
  • Transform and enrich in Apache Flink, including stateful processing and cross-stream joins that correlate events into unified lifecycle entities, with event-time handling for late and out-of-order data.
  • Enable secure, governed data access over PHI: classification and row/column controls applied as data is served to consumers, in partnership with Security and Compliance.
  • Make it reliable and observable: idempotent/replayable pipeline design, data-quality validation, runbooks, and observability the broader data team can rely on.
  • Provision as code: define the platform (streaming, processing, storage, and catalog services on AWS) in CDK with CI/CD for data pipelines, and right-size for cost against the latency SLO.
  • Partner across teams: work with upstream producers on source changes and contracts, with downstream consumers on access and data needs, and with stakeholders to turn requirements into what the platform delivers.
  • Demonstrate commitment to our core competencies of being authentic, curious, creative, empathetic and outcome oriented.

You Bring:

  • 6+ years building and operating production data systems, including demonstrated ownership of streaming or event-driven pipelines - on-call, incident response, SLOs, runbooks, and recovery, not just development.
  • Deep, production experience with Apache Kafka (MSK preferred) - partitioning, consumer groups, idempotent semantics, Kafka Connect, and replay/backfill under load.
  • Strong, hands-on production experience with Apache Flink or a comparable stateful stream processor, in Java or another JVM language - state management, checkpointing, watermarks, and exactly-once sinks.
  • AWS-native data engineering across streaming, processing, storage, and catalog services (e.g. MSK, EMR, Glue, S3, Athena), with infrastructure-as-code - AWS CDK (preferred) or Terraform - CI/CD for data pipelines, and cost awareness.
  • Comfort debugging distributed data pipelines (consumer lag, data skew, backpressure, checkpoint failures, late/out-of-order events) with observability tooling (e.g. Datadog/CloudWatch).
  • SQL and Python, and experience building and consuming REST APIs.
  • An AI-forward engineering mindset, with demonstrated hands-on use of AI-assisted and agentic development tools, an opinion on where AI adds value (and where it doesn’t), and an understanding of agentic data consumption patterns of trusted operational data - including context management, lineage, provenance, permissions, freshness.
  • Change data capture and open table formats - CDC (e.g. Debezium) plus Iceberg or Delta Lake: schema evolution, partitioning, and table maintenance.
  • Data contracts and schema governance - schema registries and technical metastore (e.g. Glue Data Catalog, Unity Catalog), compatibility rules, Avro or Protobuf, and dead-letter handling.
  • Degree in Computer Science, Information Systems or another quantitative field, and comfort on the command line / a Unix-based OS (we are 100% Mac+Linux at Gravie).
  • Excellent communication skills and demonstrated success in driving results through influence and collaboration.

Extra Credit:

  • Health insurance domain knowledge, including HIPAA Protected Health Information (PHI) and compliance frameworks governing it.
  • Familiarity with serving data to AI and agentic consumers - exposing canonical data as low-latency context or inputs for automated/agentic workloads.
  • Experience with a governance & data discovery catalog (e.g. Atlan, Alation, Collibra).
  • Previous venture-backed start-up company experience.

A LITTLE MORE ABOUT US:

  • We know healthcare. Our company was founded and is still led by industry veterans who have started and grown several market-leading companies in the space.
  • We have raised money from top tier investors who share the same long-term vision as we do of building an industry defining company that will endure over the long run. We are well capitalized.
  • Our clients love us. Customer satisfaction rates among employees using Gravie health plans consistently rank above 80% – nearly 40 points above the industry average.
  • Our culture is unique. We tend to be non-hierarchical, merit-driven, opinionated but kind people who thrive working in a high-performance, fast-paced environment. People at Gravie care deeply about making a positive impact in the lives of the people we serve.

BENEFITS

Our unique benefits program is the gravy, i.e., the special sauce that sets our compensation package apart. In addition to standard health and wellness benefits, Gravie’s package includes alternative medicine coverage, flexible PTO, up to 16 weeks paid parental leave, paid holidays, a 401k program, transportation perks, education reimbursement, and 2 days of paid paw-ternity leave.

JOB APPLICANTS

If you apply for employment with Gravie, personal information collected via our applicant tracking vendor is subject to our standalone California Job Applicant Notice at Collection, accessible directly within the application workflow and separate from this Policy.

Source: Gravie careers (Ashby)

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