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Allata
Allata
201 – 500 कर्मचारी
H1B वीज़ा प्रायोजकऑटोमोटिवलॉजिस्टिक्सस्वास्थ्य सेवा
Allata is a global consulting firm that helps organizations turn digital strategy into practical business improvements. Its teams work across strategy, customer experience, cloud and technology, data, and artificial intelligence, supporting clients with modernization, personalization, and operational efficiency. Allata serves sectors including automotive, healthcare, logistics, financial services, and high tech, drawing on experience from former IT leaders and consulting professionals to guide complex digital initiatives.
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कंपनी की नौकरियाँ

Databricks Data Platform Manager (Remote, Texas)

Lead architecture and delivery of governed Lakehouse and enterprise data warehouse platforms for Allata. Guide data pipelines, security, scalability, and data product development.

USसंयुक्त राज्यTXटेक्सासरिमोटपूर्णकालिकमध्य स्तरवरिष्ठआवश्यक भाषा: अंग्रेज़ीडेटा वैज्ञानिक
AirflowAWSAzureETLGrafanaJenkinsMS SQL ServerOraclePostgresPrometheusPySparkScalaSparkSQLUnityक्लाउड

विवरण

  • Set architecture, technology choices, reference patterns, and integration blueprints for Lakehouse and enterprise data warehouse platforms.
  • Create conceptual, logical, and physical models for multi-tenant and industry-specific data products.
  • Standardize data layers for ingestion, raw storage, curation, and serving.
  • Establish governance practices for metadata, catalogs, lineage, data contracts, and classification.
  • Define security and compliance controls for access, masking, encryption, network segmentation, and auditing.
  • Plan for platform scalability, high availability, disaster recovery, capacity, and cost management.
  • Lead selection and integration of Databricks, Delta Lake, Delta Live Tables, Fivetran, Azure Data Factory or Data Fabric, orchestration, and monitoring tools.
  • Set and enforce CI/CD practices for data assets, including tests, automated releases, and rollback plans.
  • Define batch and streaming ingestion, compaction, partitioning, and storage approaches.
  • Set observability standards for metrics, SLAs, dashboards, logs, traces, and alerts.
  • Provide technical leadership and mentorship to Data Engineering teams.
  • Review architecture and code for critical components.
  • Work with Data Product Owners and Security, Infrastructure, BI, and ML stakeholders to turn requirements into solutions and roadmaps.
  • Build, test, and deploy processing modules with Spark, PySpark or Scala, Spark SQL, and stored procedures.
  • Develop and tune data pipelines on Databricks and database platforms.
  • Apply DevOps practices, infrastructure as code, CI/CD, automated testing, and version control.
  • Resolve complex data quality, performance, and availability problems, and drive ongoing improvements.

आवश्यकताएँ

  • Prior experience as an architect or technical lead for enterprise data platforms.
  • Hands-on knowledge of Databricks technologies, including Delta Lake, Unity Catalog, Delta Live Tables, Auto Loader, and Structured Streaming.
  • Strong skills in Spark, PySpark and/or Scala, Spark SQL, and distributed job optimization.
  • Background in data warehouse and Lakehouse design.
  • Practical knowledge of Medallion, Lambda, and Kappa patterns.
  • Experience integrating SaaS, ETL, or connector tools such as Fivetran.
  • Experience with orchestration tools such as Airflow, Azure Data Factory, and Data Fabric.
  • Experience with relational and hybrid databases, including MS SQL Server, PostgreSQL, Oracle, Azure SQL, and AWS RDS/Aurora or equivalents.
  • Proficiency in data pipeline CI/CD using Azure DevOps, GitHub Actions, Jenkins, or similar tools.
  • Experience packaging and deploying artifacts such as .whl files and containers.
  • Experience with batch and streaming processing, file compaction, partitioning, and storage tuning.
  • Understanding of cloud security, IAM/RBAC, encryption, VPC/VNet concepts, and cloud networking.
  • Familiarity with observability and monitoring tools such as Prometheus, Grafana, Datadog, or native cloud services.
  • Automation experience with CI/CD pipelines and trunk-based development is a plus.
  • Advanced PySpark skills are a plus.
  • Advanced Spark workflow optimization and orchestration skills are a plus.
  • Databricks, cloud architecture, or data certifications are a plus.
  • Ability to identify, troubleshoot, and resolve complex data problems.
  • Strong collaboration and communication skills.
  • Curiosity and openness to new tools, technologies, and methods.

लाभ

  • Full-time role.
  • Equal opportunity and inclusive work environment.
  • Commitment to diversity.

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