Job description
Work Location & Reporting Address: Houston, TX 77079
Note : It will be work from office (minimum 3 days in week) and Candidate should be willing to come to Houston on Day 1 after selection.
Job Details:
Required Skills & Qualifications
Technical Skills
- Strong experience with Azure Data Platform, including:
- Azure Data Factory
- Azure Databricks
- Azure Data Lake Storage (ADLS Gen2)
- Azure Notebooks
- Hands-on expertise with:
- ETL / ELT pipeline design
- Delta Lake tables and ACID transactions
- Spark (PySpark, Spark SQL)
- Data modeling for analytics and AI
- Strong SQL skills and data modeling experience.
- Experience with CI/CD for data pipelines (Azure DevOps, Git).
- Exposure to GenAI and LLM data patterns (RAG, embeddings, text pipelines).
- Familiarity with supporting AI/ML workflows, including:
- Feature engineering
- Model training data preparation
- Inference data pipelines
- Leadership & Delivery Skills
- Proven ability to lead teams and deliver complex data platforms.
- Strong architectural thinking and problem-solving skills.
- Promote AI-first data design principles across teams.
- Excellent communication and stakeholder management abilities.
- Experience working in Agile/Scrum environments.
- Enable upskilling of teams in AI-friendly data engineering patterns.
Minimum years of experience
> 10 years
Certifications Needed :Yes
BE
Interview Process (Is face to face required?) Yes
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Frequently asked questions
Q: What skills or qualities help someone succeed as a Data Software Engineer?
A: To succeed as a Data Software Engineer, key technical skills include proficiency in programming languages such as Python, Java, or C++, as well as expertise in data structures, algorithms, and software development methodologies like Agile. Additionally, strong soft skills like effective communication, problem-solving, and collaboration are crucial, as Data Software Engineers often work with cross-functional teams and stakeholders to design, develop, and deploy data-driven solutions. By combining technical expertise with strong soft skills, Data Software Engineers can effectively drive business outcomes, innovate, and adapt to the rapidly evolving landscape of data technology.
Q: What is the career path for a Data Software Engineer?
A: A Data Software Engineer's typical career progression involves starting as a Junior Software Engineer, where they focus on developing and maintaining data-driven software applications, and gradually advancing to roles such as Senior Software Engineer, Technical Lead, or Data Architect, where they oversee large-scale data systems and lead cross-functional teams. Key opportunities for skill development include learning programming languages like Python, SQL, and Java, as well as data science tools like Hadoop, Spark, and machine learning frameworks like TensorFlow and PyTorch. Long-term, Data Software Engineers may pursue leadership roles, such as Director of Engineering or Chief Technology Officer, or transition into related fields like data science, product management, or entrepreneurship.
