Azure Data Analytics Architect

MACHINE LEARNING TECHNOLOGIES LLC; Houston (TX); On-site; USD 140,000 - 170,000; Full time

Job summary

MACHINE LEARNING TECHNOLOGIES LLC invites an experienced Azure Data Analytics Architect to design and lead analytics initiatives in the Azure Databricks ecosystem in Houston. You will own end-to-end data pipelines, work with business stakeholders, and drive data-driven decisions across the enterprise.

Responsibilities include building scalable data models, integrating Azure services, and mentoring a data engineering team while ensuring security and governance compliance.

Qualifications

• 8+ years in data ingestion and transformation pipelines with Databricks/Synapse notebooks and Azure Data Factory.

Responsibilities

• Lead architecture and implementation of analytics solutions on Azure Databricks/ Fabric.
• Collaborate with stakeholders to translate requirements into data solutions.
• Oversee end-to-end data solutions to meet business needs.
• Develop data pipelines and ETL using Databricks, PySpark, and related tools.
• Integrate Databricks with Azure services and on-prem systems.
• Provide technical leadership and mentorship to the data engineering team.
• Document architecture and data flows, ensuring security and governance compliance.
• Ensure code quality, data security, and scalability.
• Stay current with Databricks innovations.

Skills

Azure Databricks

Hadoop

Spark

Azure Data Lake

Azure Synapse

Azure Data Factory

ETL/ELT

SQL

NoSQL

CI/CD

Git

Cloud security

Communication

Problem-solving

Leadership

Tools

PySpark

Databricks SQL

Delta Lake

Azure Data Factory

Job description

Job Title

Azure Data Analytics Architect

Job Details

• Job ID: J52732
• Location: Houston, TX
• Duration: 20 Months + Extension
• Hourly Rate: Depending on Experience (DOE)
• Work Authorization: US Citizen, Green Card, OPT-EAD, CPT, H-1B,
  H4-EAD, L2-EAD, GC-EAD
• Client: To Be Discussed Later
• Employment Type: W-2, 1099, C2C

Responsibilities

• Lead the architecture, design, and implementation of advanced analytics solutions using Azure Databricks/ Fabric. The ideal candidate will have a deep understanding of big data technologies, data engineering, and cloud computing, with a strong focus on Azure Databricks along with Strong SQL.
• Work closely with business stakeholders and other IT teams to understand requirements and deliver effective solutions.
• Oversee the end-to-end implementation of data solutions, ensuring alignment with business requirements and best practices.
• Lead the development of data pipelines and ETL processes using Azure Databricks, PySpark, and other relevant tools.
• Integrate Azure Databricks with other Azure services (e.g., Azure Data Lake, Azure Synapse, Azure Data Factory) and on-premise systems.
• Provide technical leadership and mentorship to the data engineering team, fostering a culture of continuous learning and improvement.
• Ensure proper documentation of architecture, processes, and data flows, while ensuring compliance with security and governance standards.
• Ensure best practices are followed in terms of code quality, data security, and scalability.
• Stay updated with the latest developments in Databricks and associated technologies to drive innovation.

Essential Skills

• Strong experience with Azure Databricks, including cluster management, notebook development, and Delta Lake.
• Proficiency in big data technologies (e.g., Hadoop, Spark) and data processing frameworks (e.g., PySpark).
• Deep understanding of Azure services like Azure Data Lake, Azure Synapse, and Azure Data Factory.
• Experience with ETL/ELT processes, data warehousing, and building data lakes.
• Strong SQL skills and familiarity with NoSQL databases.
• Experience with CI/CD pipelines and version control systems like Git.
• Knowledge of cloud security best practices.

Soft Skills

• Excellent communication skills, with the ability to explain complex technical concepts to non-technical stakeholders.
• Strong problem-solving skills and a proactive approach to identifying and resolving issues.
• Leadership skills with the ability to manage and mentor a team of data engineers.

Nice To Have Skills

• Power BI for dashboarding and reporting.
• Microsoft Fabric for analytics and integration tasks.
• Spark Streaming for processing real-time data streams.
• Familiarity with Azure Resource Manager (ARM) templates for infrastructure as code (IaC) practices.

Experience

• Demonstrated expertise of 8+ years in developing data ingestion and transformation pipelines using Databricks/Synapse notebooks and Azure Data Factory.
• Solid understanding and hands-on experience with Delta tables, Delta Lake, and Azure Data Lake Storage Gen2.
• Experience in efficiently using Auto Loader and Delta Live tables for seamless data ingestion and transformation.
• Proficiency in building and optimizing query layers using Databricks SQL.
• Demonstrated experience integrating Databricks with Azure Synapse, ADLS Gen2, and Power BI for end-to-end analytics solutions.
• Prior experience in developing, optimizing, and deploying Power BI reports.
• Familiarity with modern CI/CD practices, especially in the context of Databricks and cloud-native solutions.

Equal Opportunity Employer

MACHINE LEARNING TECHNOLOGIES LLC is an equal opportunity employer inclusive of female, minority, disability and veterans, (M/F/D/V). Hiring, promotion, transfer, compensation, benefits, discipline, termination and all other employment decisions are made without regard to race, color, religion, sex, sexual orientation, gender identity, age, disability, national origin, citizenship/immigration status, veteran status or any other protected status. MACHINE LEARNING TECHNOLOGIES LLC will not make any posting or employment decision that does not comply with applicable laws relating to labor and employment, equal opportunity, employment eligibility requirements or related matters. Nor will MACHINE LEARNING TECHNOLOGIES LLC require in a posting or otherwise U.S. citizenship or lawful permanent residency in the U.S. as a condition of employment except as necessary to comply with law, regulation, executive order, or federal, state, or local government contract