Data Engineer

Employment type- Contract basis

Key Responsibilities

• Design, develop, and maintain scalable data pipelines using PySpark and distributed computing frameworks.
• Implement ETL processes and integrate data from structured and unstructured sources into cloud data warehouses.
• Work across Azure or AWS cloud ecosystems to deploy and manage big data workflows.
• Optimize performance of SQL queries and develop stored procedures for data transformation and analytics.
• Collaborate with Data Scientists, Analysts, and Business teams to ensure reliable data availability and quality.
• Maintain documentation and implement best practices for data architecture, governance, and security.

⚙️ Required Skills

• Programming: Proficient in PySpark, Python, and SQL, MongoDB
• Cloud Platforms: Hands-on experience with Azure Data Factory, Databricks, or AWS Glue/Redshift.
• Data Engineering Tools: Familiarity with Apache Spark, Kafka, Airflow, or similar tools.
• Data Warehousing: Strong knowledge of designing and working with data warehouses like Snowflake, BigQuery, Synapse, or Redshift.
• Data Modeling: Experience in dimensional modeling, star/snowflake schema, and data lake architecture.
• CI/CD & Version Control: Exposure to Git, Terraform, or other DevOps tools is a plus.

🧰 Preferred Qualifications

• Bachelor's or Master's in Computer Science, Engineering, or related field.
• Certifications in Azure/AWS are highly desirable.
• Knowledge of business intelligence tools (Power BI, Tableau) is a bonus.

Role: SDET

Core Testing Competencies

• Strong understanding of STLC and Agile methodologies
• Experience in Integration, System, UAT, Regression, and Sanity testing
• Hands-on experience in E-commerce application testing
• API testing using tools like Postman / SoapUI
• Mobile testing on iOS and Android (real devices/emulators)
• Cross-browser web testing

Automation Skills

• Designing and maintaining automation frameworks:
• Page Object Model (POM)
• Data-Driven and Keyword-Driven frameworks
• Programming languages: Java, JavaScript
• Web automation: Puppeteer
• Mobile automation: Appium, WebdriverIO
• CI/CD integration using Jenkins
• Backend automation using JUnit (good to have)

Tools & Technologies

• Test management & documentation: Jira, Confluence
• Defect tracking: Jira, Excel
• Proxy tools: Charles
• Databases: SQL (MySQL, PostgreSQL, Oracle) for backend validation
• Browser debugging & network inspection: Chrome DevTools

Other Key Skills

• Test documentation and bug reporting
• RTM (Requirement Traceability Matrix)
• Strong analytical and problem-solving skills

MUST-HAVES:

• LLM, AI, Prompt Engineering LLM Integration & Prompt Engineering
• Context & Knowledge Base Design.
• Context & Knowledge Base Design.
• Experience running LLM evals

NOTICE PERIOD: Immediate – 30 Days

SKILLS: LLM, AI, PROMPT ENGINEERING

NICE TO HAVES:

Data Literacy & Modelling Awareness Familiarity with Databricks, AWS, and ChatGPT Environments

ROLE PROFICIENCY:

Role Scope / Deliverables:

• Scope of Role Serve as the link between business intelligence, data engineering, and AI application teams, ensuring the Large Language Model (LLM) interacts effectively with the modeled dataset.
• Define and curate the context and knowledge base that enables GPT to provide accurate, relevant, and compliant business insights.
• Collaborate with Data Analysts and System SMEs to identify, structure, and tag data elements that feed the LLM environment.
• Design, test, and refine prompt strategies and context frameworks that align GPT outputs with business objectives.
• Conduct evaluation and performance testing (evals) to validate LLM responses for accuracy, completeness, and relevance.
• Partner with IT and governance stakeholders to ensure secure, ethical, and controlled AI behavior within enterprise boundaries.

KEY DELIVERABLES:

• LLM Interaction Design Framework: Documentation of how GPT connects to the modeled dataset, including context injection, prompt templates, and retrieval logic.
• Knowledge Base Configuration: Curated and structured domain knowledge to enable precise and useful GPT responses (e.g., commercial definitions, data context, business rules).
• Evaluation Scripts & Test Results: Defined eval sets, scoring criteria, and output analysis to measure GPT accuracy and quality over time.
• Prompt Library & Usage Guidelines: Standardized prompts and design patterns to ensure consistent business interactions and outcomes.
• AI Performance Dashboard / Reporting: Visualizations or reports summarizing GPT response quality, usage trends, and continuous improvement metrics.
• Governance & Compliance Documentation: Inputs to data security, bias prevention, and responsible AI practices in collaboration with IT and compliance teams.

KEY SKILLS:

Technical & Analytical Skills:

• LLM Integration & Prompt Engineering – Understanding of how GPT models interact with structured and unstructured data to generate business-relevant insights.
• Context & Knowledge Base Design – Skilled in curating, structuring, and managing contextual data to optimize GPT accuracy and reliability.
• Evaluation & Testing Methods – Experience running LLM evals, defining scoring criteria, and assessing model quality across use cases.
• Data Literacy & Modeling Awareness – Familiar with relational and analytical data models to ensure alignment between data structures and AI responses.
• Familiarity with Databricks, AWS, and ChatGPT Environments – Capable of working in cloud-based analytics and AI environments for development, testing, and deployment.
• Scripting & Query Skills (e.g., SQL, Python) – Ability to extract, transform, and validate data for model training and evaluation workflows.
• Business & Collaboration Skills Cross-Functional Collaboration – Works effectively with business, data, and IT teams to align GPT capabilities with business objectives.
• Analytical Thinking & Problem Solving – Evaluates LLM outputs critically, identifies improvement opportunities, and translates findings into actionable refinements.
• Commercial Context Awareness – Understands how sales and marketing intelligence data should be represented and leveraged by GPT.
• Governance & Responsible AI Mindset – Applies enterprise AI standards for data security, privacy, and ethical use.
• Communication & Documentation – Clearly articulates AI logic, context structures, and testing results for both technical and non-technical audiences.

• Managing distributors and seller and improve the efficiencies in terms of both- retention (% active, D90 retention etc.) and transaction (% transacting, count and amount of transactions from different user cohorts) of newly acquired and existing base
• Designing promotional pricing schemes, subscription packs, communication plans and taking other tactical and strategic steps to increase transactions and engagement on the platform
• Working across departments(i.e. data science, CX, sales, marketing etc.) to deliver a superior experience for distributors and sellers
• Building the needed infrastructure and continuously innovating on ways to reach new and returning users through a variety of communication channels
• Partnering with product teams throughout the organization to leverage and influence existing internal growth and engagement technologies
• Conducting competitive analysis to understand industry trends for how to engage and convert users
• Working closely with product, marketing and data science to identify the right features essential for growth of business and engagement of users
• Measuring and assessing the impact of experiments, their business impact and sharing them with leadership

Desired Candidate Profile

• B.E./ B.Tech and/or MBA
• 7 to 8 years of total experience and 2 to 5 years of experience in handling sales, business development, city operations in an operations intensive role
• People management experience
• A proactive approach to problem solving with high focus on customer empathy    

Principal Software Engineer /Architect

Axtechnosoft Private Limited

Job Description

Responsibilities: -

• You would take ownership of the existing system and scale it more than 10X over the next 2 years.
• Apply best coding standards.
• You would create the infrastructure that can serve 100s of customers and millions of data requests per hour.
• Over the next year or so, you would be able to guide a team of 5 to 15 people to accomplish your goals. Mentoring this team into a world-class engineering team would be a key part of your role.
• Your earlier experience in successfully building, deploying and running complex, large scale web or data products.
• You would work hand-in-hand with the Product Management team to build engineering capabilities that align with the evolution of the product.
• Eventually work with Data science teamwork to ensure that the algorithmic intelligence that we build is plugged into the product in an expected manner.
• Overall, you would be responsible for end-to-end architecting from Engineering standpoint.

Must have: -

• Total experience of 8+ years while relevant experience of at least 2 years.
• Have built a platform that handles at least 500k to 1 million data request an hour.
• Worked on building an infrastructure that serves 200k+ customers.
• Hands on coder.
• Expert level knowledge in at least one technology stack - Python or ideally, Java. Also Angular, React, Node.js
• Expert level knowledge with Elastic Search or NoSQL technologies like MongoDB/HBase/Cassandra/Redis/Neo4j
• Experience developing web applications.
• Knowledge of multiple front-end languages and libraries (e.g. HTML/ CSS, JavaScript, XML, jQuery)
• Working knowledge of databases (e.g. MySQL, MongoDB), web servers (e.g. Apache) and UI/UX design.
• Devops experience working with AWS / Other cloud platforms.
• Strong knowledge of API’s.
• Excellent communication and teamwork skills
• Implementing Software Engineering best practices.
• Previously worked on user facing products with scale.
• Agile methodology.
• Great attention to detail.
• Organizational skills
• An analytical mind

Good to have: -

• Working knowledge of React Red.
• Open-source technology.
• Working knowledge of AI/ ML.
• Degree in Computer Science, Statistics or relevant field.
• Experience working in a start-up environment.

Key Skills

Python

Angular Javascript

Reactor & Solids Processing

Node.js

Elastic Search

NoSQL

Web Applications

Database

Web Servers

UX/UI Design

AWS Cloud

Agile Methodology

PHP, HTML, CSS, JAVASCRIPT, AJAX, REST API, JQUERY, POSTGRESQL, MYSQL, MVC FRAMEWORK.

Responsibilities:

• Design and build advanced applications
• Work with outside data sources and APIs
• Unit-test code for robustness, including edge cases, usability, and general reliability
• Work on bug fixing and improving application performance
• Continuously discover, evaluate, and implement new technologies to maximize development efficiency
• Building reusable code and libraries for future use
• Optimization of the application for maximum speed and scalability
• Implementation of security and data protection
• Able to understand and create Documentation according to Client requirement.

Requirements:

• Ability to write clean, commented and maintainable code.
• Proven track record in designing, architecting, developing enterprise class products and solutions.
• Good understanding of MVC frameworks.
• Good understanding of front-end technologies and platforms, such as JavaScript, HTML5, and CSS3.
• Desired experience in PHP.
• Understanding accessibility and security compliance.
• User authentication and authorization between multiple systems, servers, and environments.
• Integration of multiple data sources and databases into one system.
• Management of hosting environment, including database administration and scaling an application to support load changes.
• Data migration, transformation, and scripting.
• Understanding differences between multiple delivery platforms such as mobile vs desktop, and optimizing output to match the specific platform.
• Implementing automated testing platforms and unit tests.
• Proficient knowledge of a back-end programming language.
• Proficient understanding of code versioning tools, such as Git.
• Proficient understanding of OWASP security principles.
• Proper understanding of OOPS concepts.
• Creating database schemas that represent and support business processes.
• Understanding of startup culture.
• Good team player, Quick learner.