{"id":3062245,"url":"https://alion.io/job/unisongroup-data-manager-databricks","title":"Data Manager - Databricks","company":{"id":448684,"name":"Unison Group","domain":"unisongroup.com","url":"https://alion.io/company/unisongroup","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workable","truth_index":{"grade":"B","score":75,"open_postings":71,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-10-23T05:54:15Z"}},"role":"Leadership","role_family":"Leadership","seniority":"lead","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Bengaluru, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":32000,"max_usd":83000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":33},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agile","optional":false},{"name":"CI/CD","optional":false},{"name":"Databricks","optional":false},{"name":"Delta Lake","optional":false},{"name":"ETL/ELT","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Azure","optional":true},{"name":"Azure DevOps","optional":true},{"name":"Dimensional Modeling","optional":true},{"name":"Git","optional":true},{"name":"Power BI","optional":true}],"status":"live","first_seen_at":"2026-10-16T00:00:00Z","employer_posted_date":"2026-10-16","last_verified_at":"2026-10-23T22:40:48Z","board_verified":true,"closed_at":null,"days_open":8,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":8},"description":"Role Summary\nWe are seeking an experienced Data Engineering Manager with strong Databricks and modern cloud data engineering expertise to lead the design, development and operation of scalable enterprise data solutions. The role combines technical leadership, people management, architecture oversight and delivery accountability. The successful candidate will establish engineering standards, reusable frameworks and robust practices for secure, governed, reliable and cost-efficient Lakehouse solutions.\nKey Responsibilities\nLead, mentor and support a team of data engineers, setting technical direction and encouraging engineering best practices.\nDesign, build and operate scalable data pipelines and Lakehouse solutions using Databricks, Apache Spark, Delta Lake, SQL, Python and cloud-native services.\nDefine standards for ingestion, transformation, orchestration, automated testing, deployment, observability, monitoring and production support.\nCollaborate with business, analytics, data science, architecture, security and platform teams to translate requirements into high-quality data solutions.\nChampion reusable and metadata-driven frameworks, automation, Medallion Architecture patterns and modern data engineering practices.\nEmbed data quality, security, governance, privacy and compliance controls across pipelines and data products.\nReview solution designs, code and deployment approaches to maintain consistency, resilience, maintainability and operational reliability.\nOptimize Databricks workloads for performance, scalability, reliability and cost efficiency.\nSupport Agile delivery, including backlog refinement, sprint planning, estimation, risk management, continuous improvement and technical roadmap development.\nRequired Qualifications & Experience\nBachelor's or Master's degree in Computer Science, Engineering, Information Technology, Data Science or a related discipline.\nSignificant professional experience in data engineering, including experience leading or managing data engineering teams.\nStrong hands-on experience with Databricks and Lakehouse-based architectures.\nAdvanced proficiency in Apache Spark / PySpark, SQL, Python, Delta Lake, ETL/ELT, data pipeline development and orchestration.\nStrong understanding of Medallion Architecture, distributed processing and modern cloud data-platform patterns.\nExperience implementing CI/CD, automated testing, logging, monitoring, alerting and controlled deployment practices.\nWorking knowledge of data governance, lineage, data quality, security, privacy and role-based access control.\nProven experience optimizing large-scale workloads for performance, reliability and cost.\nExperience conducting design and code reviews and establishing engineering standards.\nStrong stakeholder management, problem-solving and written and verbal communication skills.\nPreferred Qualifications\nExperience with Azure Databricks, Unity Catalog and the broader Azure data ecosystem.\nExperience building reusable, configuration-driven or metadata-driven ingestion and transformation frameworks.\nExposure to Azure DevOps, Git-based CI/CD, infrastructure as code and automated release controls.\nExperience supporting production-grade data platforms and operational support models.\nUnderstanding of dimensional modelling, enterprise data modelling and semantic or data-serving layers.\nDatabricks or relevant cloud certification.\nExperience delivering governed data products for Power BI, analytics, AI/ML or advanced analytics.","description_format":"text","description_chars":3485,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["IT Consulting & Digital Transformation"],"lifecycle":[{"event":"open","at":"2026-10-22T06:55:46Z"}],"visa":[],"liveness":{"score":63,"band":"ok","label":"Likely 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