• Engineering Director - Data Platform Jobs in Bangalore,India - 23843587

  • Zeta India

Job Description:

Engineering Director - Data Platform Bangalore

Banking Engineering

Full-time

Zeta intends to replace many legacy systems in use by banks for processing payments Banks need to leapfrog into an era of connected devices and omnipresent commerce Banking should become an integral part of the commerce and enterprise systems, thereby enabling seamless consumer and business transactions The average number of interactions an account holder may have with a bank would increase to 12-15 per day in the near term from the current average of 3-4 transactions per month These could grow to an unimaginably large number in future Most banking systems arent designed for this scale In many ways, these systems are limiting the imagination of possibilities We want this changed fundamentally, in an interoperable and regulatory compliant manner

We build large-scale transaction processing systems that can work with many current and future payment networks We build applications that help banks realise the value of this new approach early We help banks to rapidly deliver the value of these applications to their customers

Zetas platform accelerates the phenomenon of digital native neobanking, unbundling and rebundling of banking and invisible payments The platform enables the new-age financial institutes to have faster go-to-market Enables the existing financial institutes with the much-required capabilities to partner with the FinTechs and to offer a suite of modern banking experiences

As a Director of Engineering - Data Platform, you will be playing a pivotal role in enabling Zeta to deliver to its ambitions You will work with an amazing peer group that fuels this ambition You will take up initiatives that will create a lasting impact on millions of individuals across various countries Your KRAs will be People, Process and Productivity of the Data platform division at Zeta You will define and pursue objectives in these KRAs of the data engineering practice of Zeta and will deliver on the following aspects

1) Architect the complete data processing pipelines, storage and processing platform for various reporting, analytical, monitoring and machine learning use cases, for data-sets growing at 100s TB per year

2) Build and deploy the ingestion, cleansing, transformation to archival pipeline components

3) Deploy and manage the data processing frameworks and tools for reporting, analytical and machine learning workloads

4) Build, deploy and continuously enhance the data visualization, dash-boarding and distribution applications

5) Build components that can be embedded into various customer facing products to provide data-centric features like reports and analytics

6) Build the reports and dashboards for product and business teams required for day to day business analysis and for executive decision making

7) Build applications that monitor and audit the data sanity and consistency across various storages used in the transactional and analytical workloads

8) Define, document and ensure adherence to the data lifecycle management practices required for a extremely privacy-sensitive data-sets

9) Make judicious choice of the required infrastructure components considering the desired performance characteristics and the total cost of operations of the infrastructure

10) Ensure that the platform components and the supported use-cases are adequately documented and will help the relying engineering and product teams in their adoption of the data platform services

11) Operate the infrastructure in production and be fully responsible for the associated SLAs

What is the Job like You will conceive and deliver the projects required for building and supporting the data processing infrastructure
You will work with the product teams of various BUs to understand the reporting and analytics requirements of their products and define, build and enhance the corresponding application components to meet the changing requirements
You will own all the projects of the Data platform sub-division and are accountable for end-to-end execution
You will define the scope and ensure continuous adherence to the scope of projects at each phase (initiation to sustenance/maintenance phase)
You will be responsible for definition, adoption and adherence of the data lifecycle management practices
You will be responsible for guiding the teams accountable for delivering of the reports and dashboards for various business teams
You will review and audit the documentation of the services offered by the data platform
You will be accountable for continuous improvement of reliability and usability of the data and the data processing infrastructure
You will be accountable for cost optimization of the data platform
You will be accountable for velocity and quality of the projects delivered by the team
You will be accountable for production SLAs of the data platform
You will be accountable for hiring, Retention, and Engagement metrics of the team

Critical
Experience in building and operating data processing infrastructure to be run across multiple data centers, supporting mission-critical workloads for a 100 TB size datasets
A thorough understanding of various data processing workfloads and the opensource toolset available for big data processing
Lambda and Kappa architectures
Cost/benefit analysis of various processing architectures and tools
Expert level understanding of the Data lifecycle management
Mastery in building and managing high caliber teams
In-depth understanding of production operations on public cloud infrastructure
Excellent written and oral communication and penchant for technical documentation

High
Good understanding of the following
Processing and storage components like Kafka, Spark, Hadoop, Postgresql, Redshift, Cassandra, Elasticsearch and S3
Data privacy, security, and governance
Software SDLC
Agile development practices
CI/CD environment
Writing operations manual and documentation for complex software
Performance, stress, and chaos testing models
Application SLAs and Incident management practices

Nice to have
Hands on experience in using machine learning models
Hands on experience in using AWS suite of analytics, storage and machine learning services
Exposure to Terraform, Kubernetes, Docker, Jenkins X
Exposure to open source contribution and managing open source projects
Banking and Payments domain understanding

Expected experience
5 years of experience in managing high caliber engineering teams at a large scale internet or SaaS company
5 years of experience in handling big data workloads and Business intelligence systems
10 years of overall experience in software application development or data engineer or analytics in the medium to large-sized product companies

Profile Summary:

Employment Type : Full Time
Eligibility : Any Graduate
Industry : IT-Hardware/Networking, Telecom
Functional Area : IT Software : Software Products & Services
Role : Software Engineer
Salary : As per Industry Standards
Deadline : 18th Apr 2020

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