{"id":3425283,"url":"https://alion.io/job/inallmedia-data-engineer-architect-1895","title":"Data Engineer (Architect) - 1895","company":{"id":4431647,"name":"InAllMedia","domain":"inallmedia.com","url":"https://alion.io/company/inallmedia","size_band":"11-50","is_staffing_agency":false,"employer_type":"services","is_intermediary":false,"listed_via":null,"ats_vendor":"Breezy","truth_index":{"grade":"B","score":75,"open_postings":36,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-11-03T05:54:40Z"}},"role":"Data Science","role_family":"Data Science","seniority":"staff","employment_type":"full_time","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"board_field","remote_working_hours":{"label":"UTC-8 – UTC-5","utc_offset_min":-8,"utc_offset_max":-5},"hiring_geo_confidence":"structured","locations":[],"countries":[],"hiring_countries":["MX"],"hiring_countries_total":1,"salary":null,"salary_estimate":{"min_usd":51000,"max_usd":122000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":781},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Python","optional":false},{"name":"SQL","optional":false},{"name":"dbt","optional":true},{"name":"ETL/ELT","optional":true},{"name":"Snowflake","optional":true}],"status":"live","first_seen_at":"2026-03-11T16:54:01Z","employer_posted_date":"2026-03-11","last_verified_at":"2026-11-04T01:10:20Z","board_verified":true,"closed_at":null,"days_open":237,"trust":{"level":"stale","repost_count":0,"flags":["stale"],"days_open":236},"description":"About Inallmedia.com\nInallmedia.com is a global technology and design firm focused on building impactful digital solutions through remote, distributed teams across LATAM. We partner with international clients across industries, providing long-term technical expertise, product innovation, and team augmentation.\nOur teams work on high-scale platforms that require strong engineering ownership, business alignment, and measurable product impact.\nProject Overview (Project Outpost)\nYou will join a high-visibility initiative focused on maturing the organization's data landscape. The Outpost project is moving from an \"evolving\" data environment to a structured, high-performance ecosystem.\nAs a Data Architect, your mission is to solve current structural inconsistencies and define the long-term data strategy. This is not a \"maintenance\" role; it is an architectural leadership position meant to ensure data is reliable, accessible, and high-quality for both internal operational efficiency and external customer reporting. By improving schema performance and structure, you will directly enable better business decisions and robust application performance.\nKey Responsibilities\nDefine Data Strategy: Architect and implement the long-term data roadmap to transition the organization into a structured, high-performance ecosystem.\n Schema Design: Design and optimize complex data models for both transactional (operational) and analytical use cases.\nPerformance Tuning: Lead database performance tuning and structural improvements to ensure high-speed query execution and system reliability.\nIdentify Critical Insights: Use analytical intuition to independently identify business-critical data points and define clear analysis goals.\nStandardization: Establish and enforce organizational naming conventions, data governance practices, and structural consistency across the landscape.\nAutomation: Utilize Python to create automation scripts for data exploration, cleaning, and landscape management.\nCross-Functional Collaboration: Partner with Product, Backend Engineering, and Stakeholders to ensure data schemas support both business goals and application UX.\nMust-Have Skills\nAdvanced SQL Mastery: Expert-level proficiency in query design, CTEs, window functions, and complex aggregations.\n Data Modeling: Proven track record of designing scalable schemas for diverse use cases (Transactional vs. Analytical).\nOptimization Expertise: Deep knowledge of database performance tuning and structural improvements.\n Functional Python: Proficiency in using Python (loops, functions, dictionaries) for data exploration and automation tasks.\nStrategic Intuition: The ability to navigate ambiguity and independently identify how data structure impacts business outcomes.\nSelf-Direction: Proven ability to manage complex data landscapes and architectural shifts without constant supervision.\nFluent English: Strong communication skills for daily collaboration with international stakeholders.\nNice-to-Have Skills\nCloud Warehousing: Specific experience with Snowflake or similar modern cloud data warehouse environments.\nGovernance: Experience implementing formal data governance frameworks and metadata management.\nETL/ELT Optimization: Hands-on experience optimizing specific data transformation pipelines to reduce latency.\nModern Data Stack: Familiarity with tools like dbt or Airflow for managing the data lifecycle.\nLATAM Experience: Experience working in remote, distributed teams across Latin American time zones.\nTime Zone & Collaboration\nThe role requires collaboration with teams aligned to Central Time (CT), USA. 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