{"id":3365844,"url":"https://alion.io/job/true-talent-solutions-partners-data-engineer-data-product","title":"Data Engineer, Data Product","company":{"id":4415660,"name":"True Talent Solutions Partners","domain":"truetalentsolutionspartners.com","url":"https://alion.io/company/true-talent-solutions-partners","size_band":null,"is_staffing_agency":true,"employer_type":"agency","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"junior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["New York, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":180000,"max":225000,"currency":"USD","period":"year","gross":null,"usd_annual":225000},"salary_estimate":null,"experience_years_min":2,"visa_sponsorship":true,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Airflow","optional":false},{"name":"Apache Iceberg","optional":false},{"name":"Dagster","optional":false},{"name":"dbt","optional":false},{"name":"Python","optional":false},{"name":"Snowflake","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Trino","optional":false}],"status":"live","first_seen_at":"2026-10-27T18:25:18Z","employer_posted_date":"2026-10-27","last_verified_at":"2026-10-30T08:09:26Z","board_verified":true,"closed_at":null,"days_open":2,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":2},"description":"About the Role\nBuild production-ready data products from complex consumer data, working across data engineering and applied data science. Your work will help turn raw, ambiguous signals into trusted datasets that support customer-facing products and revenue-generating use cases.\nWhat You'll Do\nInvestigate unfamiliar datasets to understand their structure, coverage, relationships, and suitability for product use cases.\n\nDesign domain models and derived attributes, then build and operate ingestion and transformation pipelines with validation, observability, and backfills.\n\nEvaluate new data sources and determine how they can improve consumer data products.\n\nDevelop deep expertise in one or more data domains, such as identity, property, or consumer intent.\n\nPartner with data scientists, platform engineers, and customer-facing teams to turn ambiguous questions into scalable products.\n\nHelp hire and develop a small team of data practitioners.\n\nWhat We're Looking For\nTypically 2 to 5 years of experience in data engineering, applied data science, or analytics engineering, with strong Python and SQL skills.\n\nHands-on experience working with large, messy, multi-source datasets, including data cleaning and domain modeling.\n\nExperience building production pipelines and customer-facing data products, not only dashboards, reporting, or infrastructure systems.\n\nFamiliarity with orchestration and transformation tools such as Dagster, Airflow, or dbt; experience with Snowflake, Spark, Apache Iceberg, or Trino is relevant.\n\nA relevant computer science or engineering degree and strong technical fundamentals.\n\nExperience independently shaping ambiguous data problems, working on product or revenue-focused teams, and mentoring or developing junior teammates.\n\nStartup or high-growth company experience is helpful.\n\nCompensation & Benefits\nBase salary: $180,000 to $225,000 annually. 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