Technical Lead - Cloud Data Engineering

Indotronix International Corporation
Washington, United States of America
yesterday

Role details

Contract type
Temporary contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Senior
Compensation
$ 164K

Job location

Remote
Washington, United States of America

Tech stack

Agile Methodologies
Artificial Intelligence
Azure
Cloud Database
Data as a Services
Data Governance
ETL
Data Stores
Data Systems
Data Warehousing
DevOps
Ganglia (Software)
JMeter
Python
Log Analysis
Machine Learning
Meta-Data Management
Microsoft Software
Microsoft SQL Server
NoSQL
Powershell
Cloud Services
Azure
SQL Stored Procedures
SQL Databases
SQL Server Reporting Services
SQL Server Integration Services
SQL Server Analysis Services
T-SQL
Enterprise Data Management
Scripting (Bash/Python/Go/Ruby)
Performance Testing
Azure
Cloud Monitoring
Spark
Data Lake
PySpark
Information Technology
Data Lakehouse
Cloud Migration
Data Delivery
Api Design
Azure
Data Pipelines
Legacy Systems

Job description

We are seeking a customer-focused Technical Lead - Cloud Data Engineering to lead a team of developers in designing and implementing enterprise-scale data engineering solutions. In this role, you will work directly with business users to translate requirements into cloud-native solutions, while driving the migration of a legacy Enterprise Data Warehouse (EDW) to a modernized Microsoft Azure Cloud Data Lake platform (Medallion architecture)., * Team Leadership: Lead a team of data engineers to develop Azure Data Lake-based ETL/ELT pipelines, data extracts, and API-based data delivery.

  • Cloud Migration & Modernization: Drive the migration of legacy EDW workloads to Azure. Support design and implementation of relational, dimensional, Data Lakehouse, and NoSQL data stores.
  • Legacy EDW Operations: Ensure continued development and maintenance of legacy platforms using SQL Server, SSIS, SSRS, SSAS, and PowerShell.
  • Performance Testing & Optimization: Define ETL performance testing scope, benchmark workloads against legacy baselines, validate SLA compliance, and tune throughput using Spark UI, Azure Monitor, and Log Analytics.
  • Advanced Analytics & AI Support: Utilize Azure OpenAI, Azure Data Factory, Synapse Pipelines, and Apache Spark/Python to prepare data for advanced analytics, ML models, and interactive reporting.
  • Data Governance & DevOps: Implement data quality, security, metadata management, and audit capturing. Actively participate in Agile/DevOps processes, including Program Increment (PI) planning.

Requirements

  • Experience: Bachelor's degree in Computer Science (or related field) with 9+ years of total IT experience.
  • Team Leadership: 5+ years leading teams supporting enterprise data warehousing within Microsoft environments.
  • Client Engagement: 5+ years of direct client-facing experience capturing requirements and delivering dashboards, reports, and data solutions.
  • ETL Performance Testing: 5+ years of heavy experience benchmarking and optimizing traditional EDW and cloud data platforms using tools like JMeter, Azure Monitor, Log Analytics, and Spark UI/Ganglia.
  • Legacy Microsoft Stack: 5+ years with SQL Server (stored procedures), SSIS, SSRS, and SSAS (Cubes).
  • Languages & Scripting: 5+ years of strong proficiency in SQL, T-SQL, Python, PySpark, and PowerShell.
  • Azure Cloud Data Services: 3+ years of hands-on experience building solutions with Azure Data Lake (ADLS Gen2), Azure Synapse Analytics, Azure Data Factory (ADF), and Integration Runtime.
  • Clearance & Citizenship: Must be a capable of clear passage for a Federal Public Trust clearance.

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