Data Analytics Technical Lead

Allwyn Corp•Herndon, VA

About The Position

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.

Requirements

Extensive hands-on experience in Databricks.
Advanced data engineering skills.
Lakehouse architecture expertise.
Performance optimization skills.
Relevant Databricks certifications.
Expertise leading enterprise-scale analytics initiatives across modern cloud and big data platforms.
Full analytics ecosystem experience.
AI/ML solutions and predictive analytics experience.
Data warehousing and ETL/ELT modernization experience.
Business intelligence and visualization tools experience (Power BI and Tableau).
Cloud platforms experience (primarily AWS).
Real-time and batch data processing frameworks experience.
Strong leadership experience managing and mentoring cross-functional analytics and engineering teams.
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 (S3, Glue, Lambda, Kinesis, 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.
Focus on data quality, governance, lineage, observability, and CI/CD-driven DevOps practices.
Hands-on experience with advanced Databricks capabilities (Delta Live Tables (DLT), Unity Catalog, Workflows).
Performance tuning of distributed Spark workloads.
Deep knowledge of visualization and BI platforms (Power BI and Tableau).
Track record of mentoring engineering teams.
Databricks Certified Data Engineer Professional certification.

Responsibilities

Leading enterprise-scale analytics initiatives across modern cloud and big data platforms.
Managing and mentoring cross-functional analytics and engineering teams.
Driving delivery excellence, stakeholder alignment, and scalable data strategy execution.
Bridging technical implementation with business objectives to deliver actionable insights and enterprise data transformation outcomes.
Designing and delivering scalable, end-to-end analytics and data engineering solutions.
Building and optimizing batch, real-time, and streaming ETL/ELT pipelines within modern lakehouse architectures.
Implementing secure, high-performance, and cost-efficient cloud data platforms.
Supporting enterprise AI/ML, analytics, and reporting initiatives through curated and scalable datasets.
Establishing best practices.
Collaborating cross-functionally with architects, data scientists, BI teams, security, and business stakeholders to align technical solutions with enterprise data strategy and business objectives.