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# Technology - Senior Data Engineer

- **Company:** Indotronix Avani Group
- **Location:** Lake Buena Vista, FL, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Airflow, Amazon Web Services, Big Data, Cloud Computing, Cloud Engineering, Databases, Information Engineering, Extract Transform Load (ETL), Data Warehousing, DevOps, Github, Python (Programming Language), PostgreSQL, OpenAI, Standard Sql, SQL Databases, LangChain, Retrieval-Augmented Generation, Large Language Models, Snowflake, Prompt Engineering, Generative AI, Gitlab, Containerization, Kubernetes, Infrastructure Automation Frameworks, Information Technology, Data Management, Api Design, Software Version Control, Data Pipelines, Docker, Databricks
- **Published:** October 16, 2026
- **Apply:** https://candidateportal.ceipal.com/job-details/NgQw9WRRvTRBp0sFjP_WBoacD_vhCfCxljdjHfsQkxc

## About the Role

Bachelor's degree in Computer Science, Mathematics, Software Engineering, or related field

 - 5+ years of technology experience in data engineering roles
 - Advanced expertise in Python and SQL
 - Strong track record in developing and maintaining ELT/ETL pipelines
 - Proficient in database and data warehouse design (PostgreSQL, Snowflake)
 - Practical understanding of GenAI tools, LLMs, embeddings, prompt engineering, and vector databases/RAG architectures
 - Experience with GenAI APIs/frameworks (OpenAI, LangChain, AWS Bedrock)
 - Hands-on experience with job orchestration (Apache Airflow)
 - Familiarity with multi-environment DevOps workflows and source control (GitLab, GitHub)
 - Strong problem-solving skills and ability to communicate technical concepts effectively

Preferred Skills

 - Experience with analytic systems and big data technologies (Databricks, Snowflake)
 - Proficiency in API development and cloud architecture (AWS preferred)
 - Knowledge of Infrastructure as Code, Docker, Kubernetes, and elastic scaling
 - Experience working with large datasets and advanced data platforms, Basic Qualifications:* 5+ years of technology experience* Strong experience with ELT/ETL data pipeline development and maintenance* Proven expertise using Python and SQL* Strong understanding of database and data warehouse design and proficiency utilizing various data platforms such as PostgreSQL Snowflake etc* Solid understanding of GenAI concepts and tools (eg LLMs embeddings prompt engineering)* Understanding of vector databases or RAG (Retrieval-Augmented Generation) architectures* Experience working with GenAI APIs or frameworks (eg Open AI LangChain AWS Bedrock)* Experience with developing in a multi environment (Dev QA prod etc) and DevOps procedures for code deployment/promotion using a source control product such as GitLab or GitHub* Hands-on knowledge of job orchestration software like Apache Airflow* Experience and understanding of one or more business domains to a Docker and containerization and elastic scaling with Kubernetes or a similar
framework and with AWS* Experience working with large datasets and big data technologies such as Snowflake Databricks or similar* Demonstrated proficiency with API development* Knowledgeable on cloud architecture and product offerings preferably AWS

## Description

Join an innovative team at the forefront of data engineering and Generative AI integration. As a Senior Data Engineer, you will drive the development of advanced data solutions, collaborating with business, science, and technology teams to enable impactful analytics, machine learning, and data-driven applications. You'll be instrumental in building robust ETL/ELT pipelines, integrating GenAI tools, and producing high-quality datasets for scientific models and visualizations. This is an excellent opportunity to expand your skills in a collaborative, technology-focused environment., Gather and analyze data requirements; translate business needs into technical specifications

 - Design, develop, and maintain advanced analytic data pipelines using Python and SQL
 - Implement and optimize ETL/ELT processes for reliable data flows
 - Integrate GenAI concepts, tools, and APIs (LLMs, embeddings, RAG, OpenAI, LangChain, AWS Bedrock) into engineering workflows
 - Develop, validate, and manage datasets for science models and visualizations
 - Support and enhance data warehouse solutions leveraging platforms like PostgreSQL, Snowflake, and Databricks
 - Manage code deployment and promotion using DevOps best practices and source control tools (GitLab, GitHub)
 - Monitor and orchestrate data workflows using Apache Airflow
 - Participate in technical reviews, ensuring quality and performance of deliverables
 - Collaborate cross-functionally and communicate complex technical concepts to non-technical stakeholders