{"id":2697182,"url":"https://alion.io/job/revstar-databricks-engineer","title":"Databricks Engineer","company":{"id":35927,"name":"RevStar","domain":"revstarconsulting.com","url":"https://alion.io/company/revstar","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workable","truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":null,"employment_type":"full_time","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"board_field","remote_working_hours":{"label":"CT","utc_offset_min":-6,"utc_offset_max":-6},"hiring_geo_confidence":"inferred","locations":[],"countries":[],"hiring_countries":["AR","BR","CO","MX","CL","VE"],"hiring_countries_total":6,"salary":null,"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agile","optional":false},{"name":"Amazon S3","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"CI/CD","optional":false},{"name":"Databricks","optional":false},{"name":"Delta Lake","optional":false},{"name":"ETL/ELT","optional":false},{"name":"GCP","optional":false},{"name":"GDPR","optional":false},{"name":"HIPAA","optional":false},{"name":"MLFlow","optional":false},{"name":"Python","optional":false},{"name":"SOC 2","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Terraform","optional":false},{"name":"Airflow","optional":true},{"name":"Amazon Kinesis","optional":true},{"name":"Apache Kafka","optional":true},{"name":"Machine Learning","optional":true},{"name":"Prefect","optional":true}],"status":"closed","first_seen_at":"2026-08-25T00:00:00Z","employer_posted_date":"2026-08-25","last_verified_at":"2026-10-19T18:21:37Z","board_verified":false,"closed_at":"2026-10-19T18:21:37Z","days_open":55,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":55},"description":"Reports To: Data & AI Practice Lead\n Location: Remote (US-Based / Eastern or Central Time Zone Preferred)\nEmployment Type: Contract\nReady to build greenfield Lakehouse solutions at the bleeding edge of AI and big data? RevStar is an innovation shop and official Databricks Partner launching a dedicated, cloud-agnostic Data, ML, and AI practice. We are seeking a high-caliber Databricks Engineer to build, optimize, and deploy high-performance data pipelines and MLOps frameworks for enterprise clients across AWS, Azure, and GCP. In this role, you will work directly with data architects, scientists, and client leaders to turn complex data into scalable, production-ready AI models. Above all, the ideal candidate embodies RevStar’s core values:\nOur Core Values:\nSelf-Mastery: We hold a high bar for how we think, communicate, and improve.\nOwnership: We own outcomes, not just effort.\n Shared Destiny: We rise or fall together.\nYour Impact Pillars\nYour technical contributions are organized into four strategic pillars:\n1. Lakehouse Architecture & Pipeline Engineering\nDesign, build, and optimize scalable ETL/ELT pipelines using Apache Spark and Delta Lake across multi-cloud environments (AWS S3, Azure Data Lake, GCS).\nImplement robust Lakehouse architectures that seamlessly process both structured and unstructured data at enterprise scale.\nAutomate data ingestion and storage workflows to support downstream analytics and real-time operational reporting.\n2. Performance Optimization & Automation\nFine-tune Spark jobs for low latency, high throughput, and maximum cloud cost-efficiency.\nImplement CI/CD pipelines and Infrastructure-as-Code (Terraform, Databricks CLI) for automated deployments.\nBuild automated monitoring, alerting, and data quality validation frameworks to guarantee pipeline reliability.\n3. MLOps & AI Integration\nPartner with ML engineers and data scientists to build production-grade feature engineering pipelines.\nSupport model training, tracking, versioning, and deployment inside Databricks using MLflow.\nOperationalize AI/ML models into secure, scalable production environments for client applications.\n4. Data Governance & Client Excellence\nEnforce enterprise data security, access controls, and compliance standards (GDPR, HIPAA, SOC 2).\nEstablish best practices for data lineage, metadata management, and operational documentation.\nCollaborate with client-facing stakeholders to align technical implementations with critical business outcomes.\nRequirements\nMust-Have:\n3+ years of hands-on experience in data engineering, with a focus on big data processing and cloud-native architectures.\n2+ years of hands-on experience with Databricks, including Apache Spark, Delta Lake, and MLflow.\nDatabricks Certifications (Mandatory):\nDatabricks Certified Data Engineer Associate (or higher)\nProficiency in Python, SQL, and Spark-based frameworks.\nExperience in developing and optimizing large-scale ETL/ELT pipelines.\nStrong understanding of Lakehouse architecture and cloud-agnostic data solutions.\nFamiliarity with CI/CD pipelines and Infrastructure-as-Code (IaC) for Databricks (e.g., Terraform, Databricks CLI).\nKnowledge of data governance, security, and compliance best practices.\nExperience working in Agile development environments, following DevOps/MLOps best practices.\nNice-to-Have:\nAdditional Databricks Certifications (e.g., Databricks Certified Machine Learning Associate).\nExperience with real-time streaming solutions (e.g., Kafka, Kinesis, Event Hub).\nFamiliarity with cloud storage and orchestration tools (e.g., Apache Airflow, Prefect).\nBackground in AI/ML integration within Databricks, assisting in feature engineering and model deployment.\nExperience working in client-facing roles or consulting environments.\nBenefits\nBenefits for Full-Time W2 Positions:\nPaid Time Off - Take the time you need to recharge and stay productive.\nRemote-First Working Environment - Collaborate from anywhere while staying connected with our global team.\nComprehensive Health Coverage - Medical, Dental, Vision\n 401(k) Retirement Plan - Plan for your future with access to a company-sponsored 401(k) program.\nAnnual Learning & Development Stipend - Invest in your skills with conferences, certifications, or courses.\nPeer Mentorship & Coaching - Learn from experienced engineers, product managers, and architects to accelerate your growth.\nProfessional Growth Opportunities - Exposure to cutting-edge AWS GenAI, data, and cloud technologies across diverse industries.\nCompany Outings & Volunteer Opportunities - Build relationships and give back to the community.\nCollaborative, Innovative Culture - Work alongside top talent in a fast-paced, supportive environment that values curiosity and initiative.\nEqual Opportunity Employment\nAt RevStar, we don’t just accept differences - we celebrate them, we support them, and we thrive on them for the benefit of our employees, our customers, and our community. RevStar is proud to be an equal opportunity workplace.\nReasonable Accommodations\nRevStar is committed to providing access, equal opportunity and reasonable accommodation for individuals with disabilities in employment, its services, programs, and activities. 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