{"id":1473186,"url":"https://alion.io/job/metaphase-data-engineer-databricks","title":"Data Engineer - Databricks","company":{"id":3149061,"name":"MetaPhase","domain":"metaphase.tech","url":"https://alion.io/company/metaphase","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Jobvite","truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"middle","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":87000,"max_usd":167000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":285},"experience_years_min":3,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"CI/CD","optional":false},{"name":"Databricks","optional":false},{"name":"Delta Lake","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Python","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Agile","optional":true},{"name":"AWS","optional":true},{"name":"Azure","optional":true},{"name":"GCP","optional":true},{"name":"Git","optional":true},{"name":"Machine Learning","optional":true}],"status":"live","first_seen_at":"2026-09-29T17:38:48Z","employer_posted_date":"2026-09-29","last_verified_at":"2026-09-30T03:32:52Z","board_verified":true,"closed_at":null,"days_open":2,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":2},"description":"Description\nAt MetaPhase, we believe Quirky is Cool and being authentic is the only way to be! We take the work we do very seriously and do a lot of important mission-focused work for our clients. We are individuals with different passions and strengths who take as much joy in the work we do as from those we work with. Today, we have a team that is invested in creating new solutionsthat lean forward, challenge the status quo, but also reflect our intimate knowledge of our customers’business. Over the years we have fostered a culture in which we are united by shared values-passion, solidarity, generosity, curiosity, and boldness-and these come alive in the work we do and how we do it.\nTogether, we know our people are our difference-for our clients and our colleagues. \nAre you ready to:\nWork alongside a dedicated and diverse set of people to offer honest advice and practical guidance to our clients? \nLearn and grow by taking advantage of every opportunity available to you? \nJoin a company which prides itself on its shared values and inclusive culture? \nBe the difference and make it happen?\nRole Summary\nThe Data Engineer - Databricks will support the design, development, testing, deployment, operation, and continuous improvement of data pipelines and data products within a Databricks environment. Working under the direction of the Principal Databricks Architect / Engineer and delivery leadership, this role will convert approved data requirements into reliable, well-documented, and supportable code. The engineer will contribute to data governance, platform operations, troubleshooting, and sustainment while building practical expertisein Databricks engineering patterns and enterprise data delivery.\nWhat You Will Be Doing\nDevelop, test, deploy, and maintainbatch and streamingdata pipelines using Databricks, Python, SQL, Apache Spark, and Delta Lake.\nBuildand enhance ingestion, transformation, validation, and publishing processes that move data from source systems into governed data products and analytics-ready datasets.\nImplementapproved data models, data-quality rules, metadata, and documentation in accordance withestablished architecture and governance standards.\nConfigureand maintain Databricks notebooks, workflows, jobs, compute resources, and related deployment artifacts.\nParticipatein code reviews, peer testing, release preparation, defect remediation, and CI/CD activities.\nMonitorpipeline performance, job execution, data-quality results, and platform alerts; troubleshoot issues and support resolution of production incidents.\nCollaboratewith architects, analysts, data owners, and other engineers to clarify requirements, identifydependencies, and deliver iterative improvements.\nMaintaintechnical documentation for pipelines, data sources, transformations, interfaces, test results, and operating procedures.\nWhat We Need From You (Required)\nBachelor’s degree in a technicaldiscipline and three or more years of relevant experience in data engineering, software engineering, analytics engineering, or a related field.\nDemonstrated proficiencyin Python and SQL, with experience developing, debugging, and maintaining ETL/ELT processes and data-processing code.\nOne or more years of hands-on experience with Databricks, Apache Spark, or a comparable cloud data-engineering platform.\nExperience working with structured and/or unstructured data sources, data validation, source-to-target mapping, and production-support activities.\nDatabricks Certified Data Engineer Associate certification preferred;candidates without the certification must be willing to obtain it within threemonths of start date.\nAbility to obtain a U.S. Public Trust suitability determination.\nU.S. Citizenship Required(Clearance / Citizenship Requirements).\nBonus Points (Desired)\nExperiencewith Databricks capabilities such as Delta Lake, Auto Loader, Databricks SQL, LakeflowJobs, Unity Catalog, or streaming data pipelines.\nFamiliaritywith Git-based version control, code reviews, automated testing, CI/CD, and Agile delivery practices.\nExperiencesupporting data governance activities, including metadata documentation, data-quality checks, lineage, and access-control implementation.\nExperiencewith AWS, Azure, or Google Cloud data services and cloud-based integrations.\nExperiencesupporting regulated, public-sector, or security-sensitive data environments.\nAdditional Databricks certifications (e.g., Databricks Machine Learning Engineer Associate or Professional, Databricks Generative AI Engineer Associate)\nWork Location\nRemote (travel 5%)Education BA/BS in a Technical Discipline Clearance Requirements Must be able to obtain a U.S. Public Trust suitability determination. U.S. Citizenship Required.\nBenefits & Perks\nAt MetaPhase, we care about your well-being and success. Our benefits include generous PTO, federal holidays, parental leave, comprehensive health coverage (medical, dental, vision, life, and disability), 401(k) with companymatch, FSA/HSA options, commuter benefits, and much more.\nAbout MetaPhase\nMetaPhase is different with a purpose -demonstratinga new approachto the industry that puts employees and culture first. We continue to be recognized by industry as one of thefastest-growingand most impactful consultancies in the nation. MetaPhase is an equal opportunity employer. All qualified applicants will receive consideration without regard to race, color, religion, sex, sexual orientation, national origin, disability or veteran status, or any other factors protected\n#LinkedIN","description_format":"text","description_chars":5528,"description_truncated":false,"requirements":{"experience_years_min":3,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":true,"languages":[]},"benefits":["Parental leave"],"hiring_locations":[{"name":"United States","iso":"US","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":[],"lifecycle":[{"event":"open","at":"2026-09-29T17:38:48Z"}],"liveness":{"score":90,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.903,"p_room":1,"age_days":1,"expected_fill_days":35,"reasons":["conf:26","velocity","win:early"],"computed_at":"2026-10-01T05:45:00Z"},"pay":null,"html_url":"https://alion.io/job/metaphase-data-engineer-databricks","json_url":"https://alion.io/job/metaphase-data-engineer-databricks.json","meta":{"generated_at":"2026-10-02T01:27:58Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","usage":{"tier":"crawler","counted_by":"address","units_charged":1,"used_today":1744,"day_limit":5000,"remaining_today":3256,"minute_limit":60,"resets_at":"2026-10-03T00:00:00Z"}}}