Data Platform Engineer

Data Platform Engineer

About FinacPlus

FinacPlus 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 FinacPlus, 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 — TicketNetwork Inc

FinacPlus partners with TicketNetwork, a leading U.S.-based platform in the ticketing and event distribution ecosystem. Since 2002, TicketNetwork 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: PostgreSQL, MySQL
• NoSQL DBs: MongoDB, DynamoDB
• Expertise in query optimization, indexing, and performance tuning

• BI & Analytics Tools
• Hands-on experience with Tableau / Power BI or similar tools
• Strong understanding of analytics workflows and reporting systems

• DevOps & DataOps (Preferred)
• Experience with CI/CD pipelines and automation
• Exposure to containerization (Docker, Kubernetes)
• Familiarity with data observability and monitoring tools

Experience Requirements

• 10+ years of overall experience, with:
• Minimum 5+ years in data engineering
• Strong experience in BI / analytics engineering roles
• Proven experience in:
• Designing and delivering end-to-end data solutions
• Working on enterprise-grade data platforms
• Demonstrated ability to:
• Lead technical initiatives and mentor teams
• Work directly within product companies / long-term engagements (preferred over short-term consulting roles)

• Strong preference for candidates who:
• Provide clear project-level contributions
• Demonstrate hands-on ownership of solutions
• Show depth over tool-based superficial experience

Why Join FinacPlus

✔ Great Place to Work® Certified — collaborative, inclusive culture

✔ Exposure to global financial and data platforms

✔ Work with senior stakeholders across India, U.S. & U.K.

✔ Hybrid/Remote flexibility with strong work-life balance

✔ Competitive compensation and career growth

✔ Opportunity to build enterprise-grade, high-impact data systems

If you're an experienced backend engineer who thrives in building scalable, cloud-native systems in a global fintech environment, we'd love to hear from you.

Location: India | Work Mode: Remote

Timings: 05:30 PM – 2:30 AM IST (EST overlap)

Compensation: Best in Industry

Email your Resume: Durga Prasad: [Confidential Information]