Data Analytics Technical Lead

Allwyn

$120K — $145K *
Information Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • 5-7 years of hands-on experience with Databricks and its capabilities
  • Proficient in SQL, PySpark, and AWS cloud services including S3 and Redshift
  • Strong background in designing analytics solutions with lakehouse architecture
  • Experienced in AI/ML solutions and predictive analytics
  • Demonstrated leadership in managing cross-functional analytics teams
  • Databricks Certified Data Engineer Professional
  • Familiarity with BI tools like Power BI and Tableau

Responsibilities

  • Lead enterprise-scale analytics initiatives utilizing Databricks and cloud platforms
  • Design and implement scalable ETL/ELT pipelines for real-time and batch data processing
  • Drive delivery excellence and stakeholder engagement across analytics projects
  • Mentor analytics and engineering teams to enhance skills and performance
  • Establish best practices for data governance, quality, and CI/CD processes
  • Ensure alignment between technical implementations and business objectives
  • Provide actionable insights through curated datasets for AI/ML and reporting initiatives

Benefits

  • Flexible working arrangements
  • Professional development opportunities
  • Health and wellness programs
  • Collaborative work environment
  • Access to the latest technology and tools
Full Job Description
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.

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