{"id":28948,"url":"https://alion.io/job/mactores-aws-data-engineer-associate","title":"AWS Data Engineer (Associate)","company":{"id":6938,"name":"Mactores","domain":"mactores.com","url":"https://alion.io/company/mactores","size_band":"201-500","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Lever","truth_index":{"grade":"D","score":52,"open_postings":31,"ghost_share":0.71,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":87,"computed_at":"2026-10-16T05:45:00Z"}},"role":"Data Science","role_family":"Data Science","seniority":"junior","employment_type":"full_time","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"board_field","remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Seattle, United States"],"countries":["US"],"hiring_countries":["US"],"hiring_countries_total":1,"salary":null,"salary_estimate":{"min_usd":74000,"max_usd":162000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":54},"experience_years_min":2,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Airflow","optional":false},{"name":"Amazon Redshift","optional":false},{"name":"AWS","optional":false},{"name":"ETL/ELT","optional":false},{"name":"pySpark","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Python","optional":true}],"status":"live","first_seen_at":"2022-08-25T09:05:12Z","employer_posted_date":"2022-08-25","last_verified_at":"2026-10-16T10:55:14Z","board_verified":true,"closed_at":null,"days_open":1513,"trust":{"level":"ghost","repost_count":0,"flags":["stale","company_stale"],"days_open":1512},"description":"This role sits in our Data Platform Modernization pillar: consolidating and migrating customer data infrastructure on AWS in weeks, not quarters. Customers come to us with pipelines nobody trusts, metrics nobody agrees on, and warehouses that stall every new business question. You'll build the data products that fix that - working with business leads, analysts, and data scientists to understand the domain, then shipping pipelines and models that hold up in production.\nBecause Aedeon handles the repetitive layer source discovery, schema mapping, validation harnesses - you won't spend your early career grinding through spreadsheet audits. You'll spend it writing code that reaches production and learning judgment from engineers who own cutovers. Data quality isn't a checkbox here; it's the product.\nWhat you will do?\nWrite efficient PySpark and Amazon Glue code that ships to production.\nWrite SQL in Amazon Athena and Amazon Redshift.\nPick up new technologies and techniques and put them to work on real business problems.\nWork across engineering and business teams to build data products and services people actually use.\nDeliver projects with the team and land customer updates on time.\nWhat are we looking for?\n1 to 3 years of experience in Apache Spark, PySpark, and Amazon Glue.\n2+ years of experience writing ETL jobs using PySpark and SparkSQL.\n2+ years of experience with SQL queries and stored procedures.\nDeep understanding of the Dataframe API and the transformation functions supported by Spark 2.7+.\nYou will be preferred if you have\nPrior experience in working on AWS EMR, Apache Airflow\nCertifications AWS Certified Big Data - Specialty OR Cloudera Certified Big Data Engineer OR Hortonworks Certified Big Data Engineer\nUnderstanding of DataOps Engineering\nHow we work?\nWe run a forward-deployed model. Engineers embed with the customer's team, own outcomes from discovery through production, and carry the delivery commitment personally. Aedeon absorbs scale; engineers absorb judgment; the contract absorbs risk. As an associate, you'll work inside that model from day one shipping alongside senior engineers rather than watching from a bench. The culture is casual and steers clear of rigid corporate habits. 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