Data Analytics Technical Lead with Power BI

Allwyn Corporation

United States

12 days ago

Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Experience level

Expert

Working hours

Regular working hours

Job source

www.dice.com

Tech stack

Artificial Intelligence Amazon Web Services Amazon S3 Data Analysis Business Intelligence Development Big Data Cloud Computing Continuous Integration Data Architecture Information Engineering Extract Transform Load (ETL) Data Visualization

+14 more

Data Warehousing DevOps Machine Learning Performance Tuning Cloud Services SQL Databases Apache Spark Data Strategy Data Lakes Pyspark Data Analytics Integration Frameworks Data Pipelines Databricks

Requirements

Holds Databricks Certified Data Engineer Professional certification along with strong expertise across modern analytics ecosystems and cloud-native data platforms.

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.