Data Transformation Architect

Talworx is an emerging recruitment consulting and service firm, we are hiring for our client which provides governments, businesses, and individuals with market data, expertise, and technology solutions for confident decision-making. Our services span from global energy solutions to sustainable finance solutions. From helping our customers perform investment analysis to guiding them through sustainability and energy transition across supply chains, our solutions help unlock new opportunities and solve challenges.

Location: Hybrid work from office from nearest client branch, Preferrably from Hyderabad, Bangalore, Gurgaon.

The Team: You will be part of a rapidly growing organization, joining the team of highly motivated and professional Data Scientists and Machine Learning Engineers within Market Intelligence division. Market Intelligence provides financial and industry data, research, news and analytics to investment professionals, government agencies, corporations, and universities worldwide. We integrate news, comprehensive market and sector-specific data and analytics into a variety of tools to help clients track performance, generate alpha, identify investment ideas, understand competitive and industry dynamics, perform valuations, and assess credit risk.

The Impact: We are looking for candidates that are passionate to architect, build, scale and deploy Machine Learning Models and their associated Software Technology components that provide timely and essential intelligence to our disparate array of customers across the globe.

What’s in it for you: We provide a highly inclusive work environment where in you can bring your whole self to work to assist us in achieving its mission of being one of the leading providers of the highest quality risk evaluations and analytical information to the world’s financial markets. As an integral part of our team, you will be working on cutting edge state-of-the-art technology stack. In this role, you will work on multiple data science projects in collaboration with internal and external project owners on the product, commercial, and data team. You will be responsible for providing machine learning engineers support, create data pipeline for modeling, scale models, develop APIs to help move machine learning models in production. You will collaborate with the data scientists and production-oriented software engineers

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Responsibilities Responsibilities:

• Construct machine learning lifecycle management including data collection, normalization, and standardization within a data pipeline construction
• Architect technology components and build applications and interfaces for customer's consumption
• Experiment, develop and productionize high quality machine learning services and platforms to make huge technology and business impact.
• Develop hosting platform for machine learning models.
• Create pipelines to query and retrieve and update data for existing applications to keep them updated
• Supervise the scaling and management of the machine learning modeling ecosystem
• Work alongside data scientists and product owners to improve aspects of their lines of business through machine learning

What We’re Looking For:

• Extensive problem-solving ability in designing complex data and cloud architectures,
• Must possess strong hands on experience with Spark, AWS, Bigdata (Hadoop), Python and pyspark
• Possess excellent verbal & written communication skills
• Expertise in application, data, and infrastructure architecture disciplines
• Advanced knowledge of architecture and design across all systems
• Proficiency in multiple machine learning programming languages including Python, PySpark, or Scala
• 5 + years of experience with big-data technologies such as Hadoop, Spark, SparkML, etc
• Able to understand various data structures and common methods in data transformation
• Knowledge of industry-wide technology trends and best practices
• Ability to work in large, collaborative teams to achieve organizational goals
• Passionate about building an innovative culture
• Familiarity with MLOps and ModelOps
• Docker, Kubernetes, AWS, Python
• Familiarity with or clear interest in learning about financial Markets.