Technical Manager, Data Engineering

Mastercard

15 - 20 years

50 - 55 Lacs

pune

Posted:-1 days ago| Platform:

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Skills Required

data engineering s3 python cloud security load balancing data engineer sprint databricks firewalls data architecture sql server sql iam devops jenkins data governance agile hadoop aws etl sdlc

Work Mode

Work from Office

Job Type

Full Time

Job Description

Technical Manager, Data Engineering Background
Mastercard is on a journey to modernize and advance our Finance Technology landscape, covering Billing, Financial Planning, Accounting, Settlement, Treasury, Reporting and Analytics
This position will be responsible for developing and delivering high-impact technology solutions that align with our business and technical objectives
By collaborating with cross-functional teams, including business/product owners and other technical experts, you will ensure that our solutions meet evolving customer needs while improving performance, scalability, and reliability

Responsibilities

Manage a technical team, mentoring them, providing technical guidance, measuring performance and helping in their career growth
As a leader of Data platform / technology, providing guidance on complex technical challenges and driving resolution, ensuring solutions align with Mastercards engineering and data principles, and technical policies
Partnering with data owners, engineering and platform teams to establish robust data pipelines, implement data models, and ensure seamless integration across diverse systems and domains
Ensure alignment between business goals and technical execution, making sure features and solutions meet business requirements and customer needs
Participate in sprint planning, retrospectives, and other agile ceremonies to ensure the team is aligned and delivering efficiently
Assigning tasks to the team and ensuring delivery within time and quality- Adoption and ensure implementation by the team - best practices in software / data engineering, automated code reviews, testing, and continuous integration/continuous delivery (CI/CD)
Optimize the cost/benefit of software features and architecture, ensuring scalability, performance, and operational efficiency
Ensuring solutions align with Mastercards engineering and data principles, and technical policies
Identify opportunities for process improvements, helping to streamline workflows and enhance team productivity
Work closely with Product Owners / business to understand requirements and implement technical solutions with engineering best practices
Stay abreast of Data Platform technology trends and industry best practices to hone and maintain your talent
Participate in architectural discussions, iteration planning, and feature sizing meetings- Adhere to Agile processes and participate actively in agile ceremonies

All About You

15+ years of hands-on experience developing solutions on Cloud data platform, including Databricks, and managing teams
Proven experience as a hands-on data engineer, with a strong focus on delivering large-scale projects in an agile environment
-Hands-on experience in Databricks and deep understanding of its architecture
Design, develop and implement large-scale, high-volume, high-performance, highly available, scalable data-based solution and pipelines for the Databricks Lakehouse platform in AWS cloud
Hands-on experience with Hadoop, Nifi, pyspark
Hands-on with open table formats including Apache Iceberg and Parquet
Strong programming skills in Python and frameworks, with a focus on building scalable, reliable, and performant solutions
Experience with Bit Bucket, Jenkins
Hands-on experience developing and supporting data lakes, lakehouses, warehouses on-premise and on cloud, ETL solutions and other analytics solutions
Experience of AWS cloud infrastructure and services, and cloud-native software design
Experience with all tiers of applications deployed in the cloud, configuring network, cloud native services, infrastructure, and privileges for development teams (AWS Accounts, IAM Users and Roles, VPCs, S3 buckets, cloud native services) and Knowledge of cloud networking concepts, subnets, routing, load balancing, firewalls, and cloud security
Prior experience with financial systems, such as Oracle Financials, Oracle Fusion Cloud, and Hyperion, with experience optimizing their integration into broader data ecosystems, is a plus
Experience with data lifecycle management, including ingestion, ETL, pruning, modeling, and governance, within highly regulated environments
Expertise in modern data engineering best practices, CI/CD, automated testing, and code reviews, etc
Experience in partnering with data owners and other engineering and platform teams to build and manage a single source of truth for data, leveraging end-to-end technology stacks and best practices in data architecture
Strong programming skills in Python and frameworks, with a focus on building scalable, reliable, and performant solutions
Experience with performance engineering, ensuring systems are built to scale and meet varying demands
Knowledge of security best practices and experience in ensuring the secure development of applications
Experience in driving technical decision-making and trade-offs, balancing competing priorities such as business goals, technical constraints, and user experience
Ability to identify process inefficiencies and drive continuous improvement initiatives within the team
Experience working with development / engineering teams in a global environment
Experience on native AWS cloud services
Experience and knowledge of Bit Bucket, Rally, and Jenkins a plus-Strong understanding of cloud DevOps practices and implementation
Experience in cloud data migration for large sized enterprise data warehouse environments
Understanding of cloud data governance, compute optimization, cost control, etc
Understanding cloud security models, encryption strategy, network layers for on-prem + cloud hybrid model and other related concepts
Understanding of any one database technology - like Exadata / Oracle / Netezza / SQL server
Understanding of SDLC and experience in establishing processes, standards and governance to bring efficiency within development team

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