{"id":198901,"url":"https://alion.io/job/pivotal-data-engineer-flight-data-contract","title":"Data Engineer - Flight Data (contract)","company":{"id":35040,"name":"Pivotal","domain":"pivotal.aero","url":"https://alion.io/company/pivotal-aero","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Lever","truth_index":{"grade":"A","score":94,"open_postings":19,"ghost_share":0,"stale_share":0.053,"repost_share":0,"time_to_fill_p50_days":107,"computed_at":"2026-10-25T05:49:26Z"}},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":"contractor","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Palo Alto, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":60,"max":70,"currency":"USD","period":"hour","gross":null,"usd_annual":140000},"salary_estimate":null,"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Amazon CloudWatch","optional":false},{"name":"Amazon S3","optional":false},{"name":"AWS","optional":false},{"name":"AWS Glue","optional":false},{"name":"AWS Lambda","optional":false},{"name":"Dimensional Modeling","optional":false},{"name":"Google BigQuery","optional":false},{"name":"IAM","optional":false},{"name":"Presto","optional":false},{"name":"Python","optional":false},{"name":"Slack","optional":false},{"name":"Snowflake","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Trino","optional":false},{"name":"dbt","optional":true},{"name":"GitLab CI","optional":true},{"name":"Grafana","optional":true},{"name":"Terraform","optional":true},{"name":"Time Series","optional":true}],"status":"live","first_seen_at":"2026-08-18T20:33:12Z","employer_posted_date":"2026-08-18","last_verified_at":"2026-10-25T15:21:31Z","board_verified":true,"closed_at":null,"days_open":67,"trust":{"level":"ok","repost_count":0,"flags":[],"days_open":67},"description":"Pivotal is seeking a Data Engineer to build and operate the flight data warehouse - the system of record for telemetry off every aircraft in the fleet. Flight logs land continuously from customer and test aircraft; you will turn them into curated datasets, automated fleet health alerts, and dashboards that the firmware, GNC, battery, flight operations, and MRO teams rely on to make airworthiness and design decisions. This is a small team building production infrastructure, so you will own pipelines end to end: the data model, the services that run on it, the infrastructure as code that deploys them, and the monitoring that tells us when they break.\nResponsibilities\n Pipeline development: Build and maintain the ingest and transformation pipelines that land aircraft telemetry from S3 into the flight data warehouse (AWS Glue, Athena), including schema evolution as firmware logging changes.\nData modeling: Design and maintain curated marts - flight runs, component flight hours, vehicle modes, battery flight features - in SQL, with clear grain, documented lineage, and idempotent incremental refresh.\nFleet alerting services: Develop and operate the Python services that evaluate flight-by-flight health checks and deliver alerts to engineering and customer-facing channels via SNS and Slack.\nData quality: Own the automated quality gates - mart freshness, source-to-mart reconciliation, and watermark integrity - and block deploys that would publish incorrect fleet data.\nAnalytics enablement: Build the dashboards and query interfaces engineering teams use to monitor the fleet, and convert repeated one-off analyses into supported datasets.\n Collaboration: Work directly with firmware, GNC, battery, systems engineering, flight operations, and MRO to define what gets logged, what gets alerted on, and what “good” looks like for each signal.\nQualifications\nBachelor’s degree in Computer Science, Computer/Electrical Engineering, or a related technical discipline\n3+ years of professional data engineering experience building and operating production pipelines\nStrong SQL, including window functions and query tuning on a distributed, columnar engine (Athena/Trino/Presto, Spark, Snowflake, or BigQuery)\nProficient in Python for production services - not just notebooks: packaging, dependency management, unit tests, and code review\nHands-on experience with the AWS data stack: S3, Glue, Athena, Lambda, SNS, CloudWatch, and IAM\nDimensional modeling and warehouse design, including partitioning strategy for large tables\nExcellent analytical and written communication skills, with the ability to work across multidisciplinary teams\nPreferred Qualifications\n5+ years of relevant data engineering experience, including ownership of an on-call or operationally critical data system\nInfrastructure as code with Terraform, and building deployment pipelines in GitLab CI or equivalent\nTransformation frameworks such as dbt, and data quality/testing frameworks\nHigh-volume time-series or sensor telemetry, and observability tooling (Grafana, CloudWatch, or similar), including alert design that avoids alarm fatigue\nFamiliarity/experience with one or more of the following\nAerospace, automotive, or robotics telemetry and flight/vehicle test data\nEmbedded logging formats and decoding raw device logs (CAN, serial, or proprietary binary packet formats)\nFAA aircraft certification or continued airworthiness processes\nInterest in RC planes, quadcopters, or aviation","description_format":"text","description_chars":3469,"description_truncated":false,"requirements":{"experience_years_min":5,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Military Logistics"],"lifecycle":[{"event":"open","at":"2026-09-04T00:38:53Z"}],"visa":[],"liveness":{"score":56,"band":"ok","label":"Likely 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