{"id":861216,"url":"https://alion.io/job/szns-data-engineer","title":"Data Engineer","company":{"id":689901,"name":"SZNS Solutions LLC","domain":"szns.solutions","url":"https://alion.io/company/szns","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workable","truth_index":{"grade":"B","score":75,"open_postings":7,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-11-02T06:13:15Z"}},"role":"Data Science","role_family":"Data Science","seniority":null,"employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Reston, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":108000,"max_usd":234000,"period":"year","method":"role_country_seniority_unknown","sample_n":3718},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Airflow","optional":false},{"name":"Apache Kafka","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Flink","optional":false},{"name":"GCP","optional":false},{"name":"Java","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Rust","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Databricks","optional":true},{"name":"FedRAMP","optional":true},{"name":"Firestore","optional":true},{"name":"Google BigQuery","optional":true},{"name":"HIPAA","optional":true},{"name":"Machine Learning","optional":true},{"name":"Neo4j","optional":true},{"name":"PostgreSQL","optional":true},{"name":"Snowflake","optional":true}],"status":"live","first_seen_at":"2026-04-17T00:00:00Z","employer_posted_date":"2026-04-17","last_verified_at":"2026-11-02T07:02:55Z","board_verified":true,"closed_at":null,"days_open":199,"trust":{"level":"stale","repost_count":0,"flags":["stale"],"days_open":199},"description":"\"SZNS Solutions (pronounced \"seasons\") is a technology consulting company and Google Cloud Partner based in Reston VA. We specialize in delivering agentic AI and cloud computing solutions. Founded by ex-Googlers with engineers from Google, Amazon, and Capital One, SZNS differentiates itself particularly in AI, data engineering, blockchain, and cloud-native software application development.”\nRole Summary\nThe Data Engineer is the bedrock of intelligence operations, responsible for turning raw, unstructured data into actionable intelligence. You will embed directly with clients to build the data pipelines that power AI workflows. We build systems that don't just move data, but do it with the speed and reliability required for live and automated intelligence. Ultimately, you’ll create the foundations that will influence key strategic decisions for us and our customers.\nKey Responsibilities\nETL/ELT Pipelines: Architect and deploy pipelines to ingest, transform, and store data from high volume, disparate sources for real-time analysis\nBuild for the Enterprise: Create a highly reliable single source of truth for enterprise intelligence and enablement\nAI Workflow Enablement: Architect and optimize production-grade data foundations to support high-performance AI workflows and automated decision-making.\nOperations & Governance: Establish and automate strict data security, quality assurance, and governance processes. Design systems for high fault tolerance and rapid disaster recovery\nEfficiency: Design and model for efficient queries, resource usage, workload scheduling, and cost\nRequirements\nMinimum Qualifications\nBachelor’s degree in Computer Science, Engineering, or equivalent practical experience\n5+ years of experience in data engineering, within a cloud environment, demonstrating a clear progression from engineering into architectural design\nProficiency in SQL and strong programming skills in Python, Rust, or Java\nExperience building and maintaining data pipelines using processing/streaming frameworks (e.g., Kafka, Flink, Beam, Spark) and orchestration tools (e.g., Airflow)\nExperience architecting data stores and schemas for AI workflows (e.g., RAG)\nActive Google Cloud certifications, or willingness to obtain within one month of joining\nBuilder mentality and bias for action\nUS Citizen\nPreferred Qualifications\nDeep expertise in the Google Cloud Platform (GCP) ecosystem, specifically building streaming and batch pipelines using Dataflow (Apache Beam), Pub/Sub, BigQuery, and Cloud Composer (Airflow)\nStrong background in data modeling and architecture across relational (e.g., PostgreSQL), NoSQL (e.g., Firestore, MongoDB), and graph databases (e.g., Neo4j), including modern cloud data warehouses (e.g., BigQuery) and data lakes (e.g., GCS, Dataproc)\nDemonstrated experience setting up infrastructure for modern data science, machine learning, or Generative AI (e.g., preparing unstructured data, vector databases, RAG pipelines)\nFamiliarity with regulatory compliance frameworks (FedRAMP, HIPAA, etc.) and security strategies\nExperience with modern data platforms like Snowflake or Databricks\nBenefits\nCompetitive salary and benefits package\nHybrid work environment (MWF in-person in our Reston office)\nA collaborative and innovative work environment\nContinuous learning and development 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