Role: Data Engineer / Software Engineer / Gen AI Engineer
Location: Dallas, TX
Salary: 60–70K
JD:
Data Engineer
Associates proficient in data/ETL development and testing with hands-on PySpark and exposure to big data tools. Ability to perform below responsibilities: · Develop and execute PySpark test scripts for ETL pipelines, data transformations, and quality validations · Design & Develop PySpark test framework design focusing on reusable modules for batch processing · Prepare basic PySpark test scripts for ETL validations (e.g., row counts, null checks) · Run data validation queries on Hive and check Hadoop data loads · Create/update test cases in Zephyr and log defects in Jira/ServiceNow · Execute automated PySpark regression tests in CI/CD pipelines · Perform basic data quality checks (completeness, duplicates) using PySpark/Hive scripts/SQL queries · Perform root-cause analysis for Hadoop job failures in AutoSys scheduling and collaborate on fixes with stakeholders · set up small-scale test data(<100GB) in Hadoop · Develop Unix shell scripts for the Pyspark framework set up and scheduling
Qualification and Specialization:
Bachelor Of Science /Technology
Unique Experience from this Role:
The role offers hands-on exposure to building enterprise-scale PySpark solutions, spanning development, job automation, scheduling, governance, and production-ready data engineering practices.
Learning outcomes for the Trainee:
· Develop and optimize PySpark DataFrame–based ETL pipelines using structured and semi-structured data sources for large-scale processing. · Design reusable PySpark frameworks with effective use of transformations, actions, joins, window functions, and performance tuning techniques. · Build end-to-end batch data pipelines that cater to business functionalities and data enrichment logic · Create Unix shell scripts to drive PySpark executions with runtime arguments, logging, and failure controls. · Operate and manage scheduled Spark workloads through Autosys with job sequencing and dependency awareness. · Ensure code quality, scalability, and operational stability through configuration management, debugging, and adherence to enterprise standards.
Software Engineer
Application Developer to Design, build and configure applications to meet business process and application requirements in App Responsibilities: · Design and build software systems that have well-defined interfaces · Communicate with the tech lead, to understand the technology thoroughly · Perform unit and system testing · Work in an agile environment · Able to demonstrate high level of coding skills to handle complex scenarios · Deep understanding and experience in designing for scale Requirements: · Experienced in Micro services architecture and java with good understanding of design patterns, spring boot framework · Expertise in RESTful web services, and includes Advanced JavaScript architecture. · Knowledge of MongoDB, Kubernetes · Expertise in Java,J2EE Spring Boot, Spring Cloud, Eureka, Spring Cloud Gateway, Spring Security · Deep Understanding of service design for Cloud environment and related technologies Dockers, Kubernetes, AWS and OpenShift. · Experience with web servers Nginx and application server Tomcat. Knowledge of TLS, SSL certs. · Thorough understanding of distributed systems architecture and exposure to multiple technical disciplines including: · Unix, Linux and Windows · Databases (Postgres, Oracle and SQL) · High-Availability, Redundancy, Clustering, Disaster Recovery, Load Balancing · No SQL databases Mongo
Qualification and Specialization:
Bachelor Of Science /Technology
Unique Experience from this Role:
Designed and built cloud-native Java microservices with Spring Boot, leveraging Kubernetes and service discovery to deliver highly scalable, resilient, and secure enterprise applications.
Learning outcomes for the Trainee:
Understand the basics of Java and Spring Boot to develop simple RESTful microservices. Learn how to design and consume REST APIs using standard HTTP methods and JSON. Gain hands-on experience in writing clean, modular code following basic design patterns. Understand microservices fundamentals such as service separation, communication, and basic scalability concepts. Learn how to write and execute unit tests and participate in system testing activities. Gain exposure to Agile development practices, including sprint ceremonies and backlog-based delivery. Understand the basics of Docker and Kubernetes and how applications are deployed in cloud environments. Learn how applications interact with databases (Postgres / MongoDB) and perform basic data operations. Develop awareness of application security fundamentals, including authentication, authorization, and HTTPS. Build an understanding of production readiness concepts such as logging, monitoring, and handling failures.
Gen AI Engineer
Associates proficient in Gen AI development using Python, Langchain and exposure to Big Data tools. Ability to perform below responsibilities: Key Responsibilities · Design and develop Generative AI applications using LLMs (e.g., OpenAI, Gemini, Anthropic or Open-Source models) · Build and optimize RAG pipelines integrating structured and unstructured data · Implement prompt engineering, embeddings, and vector search solutions · Develop conversational AI solutions such as chatbots, copilots, and virtual assistants · Integrate enterprise data sources (databases, APIs, documents, data lakes) into AI pipelines · Design efficient data ingestion, indexing, and retrieval mechanisms · Develop and deploy solutions on cloud platforms (AWS, GCP, Databricks, Snowflake) · Work with business stakeholders, product owners, and data engineers to understand requirements · Participate in solution design discussions and contribute to proposal development and innovation initiatives
Qualification and Specialization:
Bachelor Of Science /Technology
Unique Experience from this Role:
The role offers hands-on exposure to building enterprise-scale Gen AI solutions, spanning development, job automation, scheduling, governance, and production-ready AI/Gen AI practices.
Learning outcomes for the Trainee:
· Develop Gen AI Applications using python-based frameworks and open source frameworks · Implement RAG based Chatbot or Gen AI Application with enterprise contextual knowledge. · Deploy Applications using CI/CD Pipeline · Ensure code quality, scalability, and operational stability through configuration management, debugging, and adherence to enterprise standards.
