Allwyn Corporation
Data Analytics Technical Lead
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Data Analytics Technical Lead, remote, long-term contract, offering competitive pay. Requires extensive experience in Databricks, AWS, AI/ML solutions, data warehousing, and leadership in analytics. Must hold Databricks Certified Data Engineer Professional certification.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
Unknown
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🗓️ - Date
May 15, 2026
🕒 - Duration
Unknown
-
🏝️ - Location
Remote
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📄 - Contract
Unknown
-
🔒 - Security
Unknown
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📍 - Location detailed
United States
-
🧠 - Skills detailed
#Databricks #Leadership #SQL (Structured Query Language) #Delta Lake #Data Engineering #Spark SQL #Data Processing #Data Quality #Data Strategy #Microsoft Power BI #Strategy #Visualization #Observability #Security #AWS (Amazon Web Services) #Data Science #Cloud #"ETL (Extract #Transform #Load)" #Datasets #PySpark #Redshift #Big Data #DevOps #S3 (Amazon Simple Storage Service) #Scala #Spark (Apache Spark) #Batch #AI (Artificial Intelligence) #BI (Business Intelligence) #Tableau #Lambda (AWS Lambda) #ML (Machine Learning)
Role description
Position: AWS Data Analytics Technical Lead
Location: Remote
Duration: Long Term
Data Analytics Technical Lead with extensive hands-on experience in Databricks, including advanced data engineering, Lakehouse architecture, and performance optimization, supported by relevant Databricks certifications. Proven expertise leading enterprise-scale analytics initiatives across modern cloud and big data platforms.
Well-rounded background spanning the full analytics ecosystem, including:
• AI/ML solutions and predictive analytics
• Data warehousing and ETL/ELT modernization
• Business intelligence and visualization tools such as Power BI and Tableau
• Cloud platforms primarily AWS
• Real-time and batch data processing frameworks.
Strong leadership experience managing and mentoring cross-functional analytics and engineering teams, driving delivery excellence, stakeholder alignment, and scalable data strategy execution. Adept at bridging technical implementation with business objectives to deliver actionable insights and enterprise data transformation outcomes.
Proven technical leadership in designing and delivering scalable, end-to-end analytics and data engineering solutions leveraging Databricks, Delta Lake, PySpark, SQL, and AWS cloud services including S3, Glue, Lambda, Kinesis, and Redshift. Extensive experience building and optimizing batch, real-time, and streaming ETL/ELT pipelines within modern lakehouse architectures.
Strong expertise in hands on implementation of secure, high-performance, and cost-efficient cloud data platforms with a focus on data quality, governance, lineage, observability, and CI/CD-driven DevOps practices. Hands-on experience with advanced Databricks capabilities including Delta Live Tables (DLT), Unity Catalog, Workflows, and performance tuning of distributed Spark workloads.
Experienced in supporting enterprise AI/ML, analytics, and reporting initiatives through curated and scalable datasets, with deep knowledge of visualization and BI platforms including Power BI and Tableau.
Recognized leader with a track record of mentoring engineering teams, driving delivery excellence, establishing best practices, and collaborating cross-functionally with architects, data scientists, BI teams, security, and business stakeholders to align technical solutions with enterprise data strategy and business objectives.
Holds Databricks Certified Data Engineer Professional certification along with strong expertise across modern analytics ecosystems and cloud-native data platforms
Position: AWS Data Analytics Technical Lead
Location: Remote
Duration: Long Term
Data Analytics Technical Lead with extensive hands-on experience in Databricks, including advanced data engineering, Lakehouse architecture, and performance optimization, supported by relevant Databricks certifications. Proven expertise leading enterprise-scale analytics initiatives across modern cloud and big data platforms.
Well-rounded background spanning the full analytics ecosystem, including:
• AI/ML solutions and predictive analytics
• Data warehousing and ETL/ELT modernization
• Business intelligence and visualization tools such as Power BI and Tableau
• Cloud platforms primarily AWS
• Real-time and batch data processing frameworks.
Strong leadership experience managing and mentoring cross-functional analytics and engineering teams, driving delivery excellence, stakeholder alignment, and scalable data strategy execution. Adept at bridging technical implementation with business objectives to deliver actionable insights and enterprise data transformation outcomes.
Proven technical leadership in designing and delivering scalable, end-to-end analytics and data engineering solutions leveraging Databricks, Delta Lake, PySpark, SQL, and AWS cloud services including S3, Glue, Lambda, Kinesis, and Redshift. Extensive experience building and optimizing batch, real-time, and streaming ETL/ELT pipelines within modern lakehouse architectures.
Strong expertise in hands on implementation of secure, high-performance, and cost-efficient cloud data platforms with a focus on data quality, governance, lineage, observability, and CI/CD-driven DevOps practices. Hands-on experience with advanced Databricks capabilities including Delta Live Tables (DLT), Unity Catalog, Workflows, and performance tuning of distributed Spark workloads.
Experienced in supporting enterprise AI/ML, analytics, and reporting initiatives through curated and scalable datasets, with deep knowledge of visualization and BI platforms including Power BI and Tableau.
Recognized leader with a track record of mentoring engineering teams, driving delivery excellence, establishing best practices, and collaborating cross-functionally with architects, data scientists, BI teams, security, and business stakeholders to align technical solutions with enterprise data strategy and business objectives.
Holds Databricks Certified Data Engineer Professional certification along with strong expertise across modern analytics ecosystems and cloud-native data platforms
