Data Engineer

Location: India - Hyderabad

Career Category

Engineering

Level 4 Data Engineer

What you will do

Let’s do this. Let’s change the world. In this vital role you will be responsible for designing, building, maintaining, analyzing, and interpreting data to provide actionable insights that drive business decisions. This role involves working with large datasets, developing reports, supporting and performing data governance initiatives and, visualizing data to ensure data is accessible, reliable, and efficiently managed. The ideal candidate has deep technical skills, experience with database technologies, and a deep understanding of data architecture and ETL processes.

Roles & Responsibilities

Design, develop, and maintain data solutions for data generation, collection, and processing

Be a crucial team member that assists in design and development of the data pipeline

Build data pipelines and ensure data quality by implementing ETL processes to migrate and deploy data across systems

Contribute to the design, development, and implementation of data pipelines, ETL/ELT processes, and data integration solutions

Hands-on experience designing, developing, and implementing AI solutions using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), vector search, tokenization, prompt engineering, and AI-assisted development tools such as OpenAI Codex, GitHub Copilot, or equivalent platform.

Take ownership of data pipeline projects from inception to deployment, manage scope, timelines, and risks

Collaborate with cross-functional teams to understand data requirements and design solutions that meet business needs

Develop and maintain data models, data dictionaries, and other documentation to ensure data accuracy and consistency

Implement data security and privacy measures to protect sensitive data

Leverage cloud platforms (AWS preferred) to build scalable and efficient data solutions

Collaborate and communicate effectively with product teams

Collaborate with Data Architects, Business SMEs, and Data Scientists to design and develop end-to-end data pipelines to meet fast-paced business needs across geographic regions

Identify and resolve complex data-related challenges

Adhere to best practices for coding, testing, and designing reusable code/component

Explore new tools and technologies that will help to improve ETL platform performance

Participate in sprint planning meetings and provide estimations on technical implementation

What we expect of you

We are all different, yet we all use our unique contributions to serve patients.

Basic Qualifications

Master’s/ Bachelor's degree and 5 - 9 years of Computer Science, IT or related field experience

Preferred Qualifications

Must-Have Skills

• Hands-on experience with big data technologies and platforms, such as Databricks, Apache Spark (PySpark, SparkSQL), workflow orchestration, performance tuning on big data processing
• Proficiency in data analysis tools (eg. SQL) and experience with data visualization tools
• Excellent problem-solving skills and the ability to work with large, complex datasets
• Solid understanding of data governance frameworks, tools, and best practices.
• Knowledge of data protection regulations and compliance requirements

Good-to-Have Skills

Experience with ETL tools such as Apache Spark, and various Python packages related to data processing, machine learning model development

Good understanding of data modeling, data warehousing, and data integration concepts

Knowledge of Python/R, Databricks, SageMaker, cloud data platforms

Hands-on experience designing, developing, and implementing AI solutions using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), vector search, tokenization, prompt engineering, and AI-assisted development tools such as OpenAI Codex, GitHub Copilot, or equivalent platform.

Professional Certifications

Certified Data Engineer / Data Analyst (preferred on Databricks or cloud environments)

Soft Skills

• Excellent critical-thinking and problem-solving skills
• Good communication and collaboration skills
• Demonstrated awareness of how to function in a team setting
• Demonstrated presentation skills
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