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Databrick Architect

E-Solutions

Role : Databrick Architect

Location : Tarrytown New York (Onsite)

Have you got what it takes to succeed The following information should be read carefully by all candidates.

Key Responsibilities & Skills

  • Lead enterprise-scale data platform modernization initiatives, driving migration from AWS EMR, Apache NiFi, and legacy ETL frameworks to the Databricks Lakehouse Platform.
  • Architect and implement scalable Lakehouse solutions using Databricks, Delta Lake, Unity Catalog, and Databricks Workflows.
  • Design and govern end-to-end data pipelines for batch, streaming, CDC, and real-time data integration workloads.
  • Provide architecture leadership for large-scale AWS-based data ecosystems leveraging S3, IAM, Redshift, Glue Catalog, Airflow, and Databricks.
  • Develop enterprise data architecture standards covering data modelling, metadata management, lineage, governance, security, and compliance.
  • Drive adoption of Databricks best practices including Delta Live Tables (DLT), Auto Loader, Unity Catalog, Serverless Compute, Lakehouse Federation, and advanced optimization techniques.
  • Lead replatforming and migration programmes involving PySpark applications, Airflow DAGs, EMR workloads, Redshift integrations, and NiFi pipelines.
  • Partner closely with business stakeholders, enterprise architects, product owners, and data science teams to define technology roadmaps and target architectures.
  • Establish governance frameworks using Unity Catalog, data quality controls, observability, monitoring, and operational excellence practices
  • Provide technical leadership, mentoring, architecture reviews, design governance, and solution sign-offs across multiple delivery teams.
  • Lead architecture workshops, executive presentations, solution assessments, and technology evaluations.

Mandatory Technical Skills

  • Databricks Lakehouse Platform
  • Delta Lake, Delta Live Tables (DLT)
  • Unity Catalog
  • Databricks Workflows
  • Auto Loader
  • PySpark, Spark SQL, Python
  • AWS (S3, IAM, Glue, Redshift, EMR, Lambda)
  • Apache Airflow
  • CDC & Data Migration Frameworks
  • Data Governance & Security
  • CI/CD, GitHub, Jenkins

JD:

  • Lead enterprise-scale Databricks Lakehouse Architecture design and implementation on AWS.
  • Drive large-scale data platform modernisation and cloud transformation initiatives.
  • Architect scalable Medallion Architecture (Bronze, Silver, Gold) data platforms.
  • Lead migration of legacy EMR, NiFi, Redshift, and ETL workloads to Databricks.
  • Design high-performance batch and real-time data processing solutions.
  • Build robust ingestion frameworks using Auto Loader, Delta Lake, and Structured Streaming.
  • Define enterprise data governance and security standards using Unity Catalog.
  • Architect metadata-driven and reusable PySpark-based ETL/ELT frameworks.
  • Establish best practices for performance tuning, scalability, and cost optimisation.
  • Design and implement data quality, lineage, and observability frameworks.
  • Drive adoption of CI/CD, DevOps, Infrastructure as Code, and automation practices.
  • Collaborate with business, analytics, and engineering teams to define target-state architectures.
  • Conduct architecture reviews and provide technical leadership across multiple projects.
  • Mentor architects and senior engineers on Databricks and AWS best practices.
  • Design secure and scalable solutions leveraging AWS services (S3, Glue, Athena, Lambda, IAM, Redshift).
  • Implement and govern enterprise-wide data access, compliance, and security controls.
  • Evaluate and adopt latest Databricks capabilities such as DLT, Lakehouse Federation, Serverless, and MLflow.
  • Enable AI/ML, Generative AI, and advanced analytics use cases on the Lakehouse platform.
  • Create architecture roadmaps, migration strategies, standards, and governance frameworks. xhyhwjd
  • Act as the primary technical advisor for customer leadership on data strategy and platform evolution.

Vacancy posted 4 days ago
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