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Job Description & How to Apply Below
About Finac Plus
Finac Plus is a Great Place to Work® Certified organization — a recognition of our people first culture, collaborative environment, and focus on professional growth. We provide high-end virtual business process and technology services to leading global clients across finance, banking, mortgage, research, and data services. At Finac Plus, you’ll work with world-class talent, cutting-edge technology, and international stakeholders — while still enjoying the openness, agility, and career visibility of a fast-growing company.
About Our Client — Ticket Network Inc
Finac Plus partners with Ticket Network, a leading U.S.
-based platform in the ticketing and event distribution ecosystem. Since 2002, Ticket Network has enabled promoters, venues, and resale operators to scale their businesses through advanced e-commerce technology, affiliate distribution models, and high-performance data platforms.
This role offers the opportunity to build and scale enterprise-grade data platforms that power business intelligence, analytics, and strategic decision-making in a high-volume, real-time environment.
Role Overview
We are looking for a Data Platform Engineer with strong experience in data engineering, analytics platforms, and solution design, who can architect, build, and scale enterprise data systems.
This is a senior-level role, requiring hands-on expertise along with the ability to lead technical initiatives, mentor teams, and drive data strategy. The ideal candidate brings deep experience in data pipelines, BI systems, cloud platforms, and large-scale data architecture, along with a strong understanding of business use cases
Key Responsibilities
Data Engineering & Platform Development
Design, build, and scale robust data pipelines and ETL/ELT workflows
Develop and maintain high-performance, scalable data platforms
Architect data lakes, data warehouses, and real-time data processing systems
Implement data ingestion frameworks for structured and unstructured data sources
Optimize data processing for performance, scalability, and cost efficiency
Architecture & Solution Design
Lead end-to-end data architecture design for analytics and BI use cases
Define data models, schemas, and governance frameworks
Design batch and real-time processing systems using modern architectures
Evaluate and implement best-fit tools and technologies for evolving business needs
Business Intelligence & Analytics Enablement
Partner with stakeholders to deliver high-quality, reliable data for BI and reporting
Enable self-service analytics capabilities across business teams
Support integration with BI tools such as Tableau / Power BI
Translate business requirements into scalable data solutions
Leadership & Collaboration
Provide technical leadership and mentorship to data engineering teams
Collaborate with data scientists, analysts, product, and engineering teams
Drive best practices in coding, design, and data governance
Participate in architecture discussions and strategic decision-making
Platform Reliability & Optimization
Ensure data quality, integrity, and consistency across systems
Monitor and troubleshoot data pipelines and platform issues
Implement automation, monitoring, and alerting mechanisms
Continuously improve system reliability and performance
Technical Skills & Requirements
Core Data Engineering
Strong experience in data engineering and BI development
Expertise in ETL/ELT frameworks and data pipeline design
Strong proficiency in SQL (advanced level mandatory)
Hands-on experience in Python / Java / Scala
Data Architecture & Modeling
Deep understanding of:
Data Warehousing concepts
Data Modeling (star schema, snowflake schema)
Data Lakes and modern data architectures
Experience designing enterprise-scale data systems
Cloud & Big Data Technologies
Strong experience with AWS or Azure (mandatory)
Experience with :
AWS services (Redshift, S3, Glue, Lambda)
Big data tools (Apache Spark, Kafka)
Experience working with large-scale distributed data systems
Databases & Storage
Strong experience with:
Relational DBs:
Postgre
SQL, MySQL
No
SQL DBs:
Mongo
DB, DynamoDB
Expertise in query optimization, indexing, and performance tuning
BI & Analytics…
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