Apptad Data Engineer Lead

Apptad Inc

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profile Job Location:

Palo Alto, CA - USA

profile Monthly Salary: Not Disclosed
Posted on: 30+ days ago
Vacancies: 1 Vacancy

Job Summary

Role: Data Engineer Lead

Location: Palo Alto CA

Role Summary

We are seeking an experienced Data Engineer Lead to join our onshore team and drive the design

development and optimization of enterprise data solutions using Microsoft Azure and Microsoft

Fabric. The ideal candidate will lead data engineering efforts mentor junior engineers and

collaborate with cross-functional teams to deliver scalable and secure data platforms.

Key Responsibilities

- Lead the design and implementation of data pipelines and ETL processes using Azure Data

Factory Synapse and other Azure services.

- Architect and optimize data models and storage solutions for performance and scalability.

- Integrate data flows within Microsoft Fabric for unified analytics and reporting.

- Collaborate with stakeholders to gather requirements and translate them into technical solutions.

- Ensure data quality security and compliance across all data engineering activities.

- Mentor and guide junior data engineers in best practices and technical execution.

- Troubleshoot and resolve data workflow issues and performance bottlenecks.

Required Skills

- Extensive experience with Azure Data Services (Data Factory Synapse Databricks etc.).

- Strong knowledge of Microsoft Fabric and its integration capabilities.

- Proficiency in SQL Python and Spark for data transformation and analysis.

- Experience with CI/CD pipelines and DevOps practices in data engineering.

- Understanding of data governance lineage and metadata management

Role: Data Engineer Lead Location: Palo Alto CA Role Summary We are seeking an experienced Data Engineer Lead to join our onshore team and drive the design development and optimization of enterprise data solutions using Microsoft Azure and Microsoft Fabric. The ideal candidate will lead data enginee...
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Key Skills

  • Apache Hive
  • S3
  • Hadoop
  • Redshift
  • Spark
  • AWS
  • Apache Pig
  • NoSQL
  • Big Data
  • Data Warehouse
  • Kafka
  • Scala