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Shrive Technologies · 9 hours ago

Data Architect

Fremont, CA

Contract

Onsite

Senior Level, Lead/Staff

12+ years exp

Shrive Technologies is seeking a Data Architect to design and implement enterprise-grade data solutions using Azure and Microsoft Fabric. The role involves architecting data pipelines, developing scalable data processing frameworks, and ensuring data quality and governance.

AccountingFinanceInformation TechnologySoftwareStaffing Agency

No H1B

Hiring Manager

Ravinder Reddy Kolan

Responsibilities

Design and implement end-to-end data architecture for batch and real-time data processing to implement enterprise-grade data solutions using Azure and Microsoft Fabric

Design, build, and optimize ETL/ELT pipelines for ingestion, transformation, and publishing using ADF, Spark, and Databricks

Architect and optimize data pipelines using Azure Data Factory (ADF)

Develop and manage scalable data processing frameworks using Databricks and Apache Spark

Develop efficient data transformation logic using PySpark and Spark SQL

Build reusable, high-performance data models for analytics and reporting

Develop and maintain data ingestion, transformation, and orchestration workflows

Ensure data quality, consistency, security, and governance across platforms

Define and enforce data engineering best practices, including CI/CD, versioning, testing, and monitoring

Mentor and guide data engineers, fostering a culture of innovation and excellence

Collaborate with data engineers, analysts, data scientists, and business stakeholders

Qualification

Azure Data FactoryAzure DatabricksPySparkAzure SynapseAzure SQLETL/ELT toolsSQLData warehousingData governancePythonSpark SQLPower BITableauCommunication skillsProblem-solving skills

Required

12 + years of IT experience in the Development/ Architecture Role

5+ years of Proven experience in Data Engineering and architecture roles (with Azure Data Factory, Azure Databricks & PySpark, Azure Synapse and Azure SQL)

Strong Experience with ETL/ELT tools like ADF, Informatica, Talend etc., and data warehousing technologies like Azure Synapse, Azure SQL, Amazon Redshift, Snowflake, Google Big Query etc

Strong hands-on experience with Azure Data Factory (ADF) for data orchestration (for building and managing pipelines), Azure Databricks for big data processing and analytics, and Apache Spark for distributed data processing

Adept in with big data tools (Databricks, Spark etc.)

Experience with Power BI, Tableau/OBIEE etc

Proficiency in PySpark, Python, and Spark SQL

Experience with CI/CD pipelines for data platforms

Solid understanding of data warehouse best practices, development standards and methodologies

Strong expertise in SQL and relational data modeling

Experience designing data lakes, data warehouses, or Lakehouse architectures

Good understanding of data governance, metadata management, and security best practices

Solid understanding of distributed data processing and performance tuning

Experience with ETL/ELT patterns and best practices

Strong analytical, problem-solving skills and ability to work in a fast-paced, dynamic environment

Excellent communication and documentation skills