{"id":57169,"url":"https://alion.io/job/mutt-data-data-engineer-lead-databricks-eng","title":"Data Engineer Lead - Databricks - Eng","company":{"id":19043,"name":"Mutt Data","domain":"muttdata.ai","url":"https://alion.io/company/mutt-data","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Lever","truth_index":{"grade":"B","score":79,"open_postings":12,"ghost_share":0,"stale_share":0.833,"repost_share":0,"time_to_fill_p50_days":33,"computed_at":"2026-10-17T05:46:00Z"}},"role":"Data Science","role_family":"Data Science","seniority":"lead","employment_type":null,"work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"board_field","remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Argentina"],"countries":["AR"],"hiring_countries":["AR"],"hiring_countries_total":1,"salary":null,"salary_estimate":{"min_usd":52000,"max_usd":118000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":662},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Amazon Redshift","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"Databricks","optional":false},{"name":"GCP","optional":false},{"name":"Looker","optional":false},{"name":"Machine Learning","optional":false},{"name":"Python","optional":false},{"name":"Spark","optional":false},{"name":"Tableau","optional":false}],"status":"live","first_seen_at":"2026-04-15T16:54:21Z","employer_posted_date":"2026-04-15","last_verified_at":"2026-10-17T07:58:33Z","board_verified":true,"closed_at":null,"days_open":184,"trust":{"level":"stale","repost_count":0,"flags":["stale"],"days_open":184},"description":"Join Our Data Products and Machine Learning Development Remote Startup!\nMuttdata is a dynamic startup committed to crafting innovative systems using cutting-edge Big Data and Machine Learning technologies.\nWe’re looking for a Data Engineer Lead to help take our expertise to the next level. If you consider yourself a data nerd like us, we’d love to connect!\nWhat We Do\nLeveraging our expertise, we build modern Machine Learning systems for demand planning and budget forecasting.\nDeveloping scalable data infrastructures, we enhance high-level decision-making, tailored to each client.\nOffering comprehensive Data Engineering and custom AI solutions, we optimize cloud-based systems.\nUsing Generative AI, we help e-commerce platforms and retailers create higher-quality ads, faster.\nBuilding deep learning models, we enhance visual recognition and automation for various industries, improving product categorization, quality control, and information retrieval.\nDeveloping recommendation models, we personalize user experiences in e-commerce, streaming, and digital platforms, driving engagement and conversions.\nOur Partnerships\nAmazon Web Services\nAstronomer\nDatabricks\nOur Values\n We are Data Nerds\n We are Open Team Players\n We Take Ownership\n We Have a Positive Mindset\nCurious about what we’re up to? Check out our case studies and dive into ourblog post to learn more about our culture and the exciting projects we’re working on!\nResponsibilities\nLead end-to-end data migration initiatives, ensuring a smooth, secure, and business-aligned transition.\nDefine and communicate data architecture decisions, evaluating impacts, risks, and performance considerations across cloud data platforms such as AWS Redshift, Databricks, and related technologies.\nCoordinate the discovery and documentation of dependencies, schema inventories, data flows, and critical processes involved in migration efforts.\nOwn migration and cutover planning, ensuring all activities, validations, and contingency measures are properly defined and executed.\nServe as the primary liaison between engineering, analytics, product, and business stakeholders, facilitating clear communication and alignment throughout the project lifecycle.\nTranslate technical changes in data pipelines, data warehouses, and platform architecture into clear business impact assessments.\nDefine and document assumptions, requirements, and acceptance criteria to ensure successful migration outcomes.\nOversee data validation processes to guarantee the accuracy, consistency, and integrity of migrated datasets against source-of-truth systems.\nProactively identify, assess, and mitigate migration-related risks, escalating blockers and dependencies when necessary to maintain project timelines and quality standards.\nDrive problem-solving and decision-making in fast-paced, ambiguous environments, helping cross-functional teams stay focused on priorities and deliverables.\nCreate, maintain, and improve project documentation, including migration runbooks, testing strategies, rollback plans, and operational procedures.\nProvide regular project status updates to technical and executive stakeholders, ensuring transparency around progress, risks, and next steps.\nPromote data governance, quality, and operational best practices throughout the migration lifecycle.\nAlign engineers, analysts, and product stakeholders around priorities, timelines, and delivery expectations to ensure successful project execution.\nRequired Skills\nExperience in Data Engineering, including building and optimizing data pipelines.\nExperience working with Databricks, Python, and Spark, building batch and streaming.\nAdvanced English Level.\nFamiliarity with a BI visualization tool like Looker or Tableau.\nPerks\nRemote-first culture - work from anywhere! 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