Senior Data Engineer

Primesoft Solutions; Hyderabad; On-site; INR 2,400,000 - 4,200,000; Full time

Job summary

PrimeSoft Solutions, Inc. is seeking a Senior Data Engineer to own the end-to-end data platform, from raw ingestion to trusted datasets. You will design, build, and maintain scalable data pipelines and data models powering analytics across the organization.

Ideal candidates will have 6–10 years of experience, strong SQL and data warehousing expertise, and a proactive, architecture-minded approach in a fast-paced environment.

Qualifications

• BE/BTech, ME/MTech, BSc, MSc required.
• Senior Data Engineer with 6–10 years of experience in data engineering.
• Proficient in SQL, data warehousing concepts, and data modeling.

Responsibilities

• Design, build, and maintain end-to-end data pipelines from ingestion to curated data models.
• Develop scalable data transformation layers using modern frameworks.
• Optimize data warehouse schemas to support analytics.
• Write production-grade SQL and optimize complex queries.
• Manage orchestration workflows and data lineage.
• Implement data quality, monitoring, and reliability practices.

Skills

SQL

Data warehousing

ETL/Transformation

dbt

SQLMesh

Data modeling

Workflow orchestration

Data quality

LLMs in development

Education

BE/BTech

ME/MTech

BSc

MSc

Tools

dbt

SQLMesh

Job description

About PrimeSoft:

PrimeSoft Solutions, Inc. is an outsourced product development and software services provider. We offer Product Development, Enterprise Applications, Mobile Applications,Quality Assurance and DevOps Support Services to clients from venture funded startups to publicly traded companies in Networking, Telecom, Healthcare and Banking.

Designation

Senior Data Engineer

Experience

6 to 10 years

Qualification

BE/B tech, ME/M tech, Bsc, Msc.

Location

Hyderabad, Bangalore and Mumbai

Job Description

As a Senior Data Engineer, you will own the end-to-end data platform, from raw data ingestion through transformation to trusted, business-ready datasets. You will be responsible for designing, building, and maintaining scalable, reliable, and high-quality data pipelines that power analytics and decision-making across the organization.

This role requires someone who can make sound architectural decisions, balance trade-offs, and deliver production-grade solutions in a fast-paced environment. You'll partner closely with analysts, engineers, and business stakeholders, ensuring data solutions are reliable, maintainable, and aligned with business needs. A strong bias for action, systems thinking, and expertise in modern data engineering practices are essential.

Key Responsibilities

• Design, build, and maintain end-to-end data pipelines from ingestion to curated, trusted data models.
• Develop scalable and maintainable data transformation layers using modern transformation frameworks.
• Design and optimize data warehouse schemas and data models to support reporting and analytics.
• Write highly efficient, production-grade SQL and optimize complex queries for performance.
• Build, maintain, and monitor orchestration workflows, ensuring proper dependency management and data lineage.
• Implement data quality, validation, monitoring, and reliability practices to ensure trusted datasets.
• Make architecture and design decisions while balancing scalability, maintainability, and delivery speed.
• Collaborate closely with analysts, engineers, and business stakeholders to understand requirements and translate them into robust data solutions.
• Proactively identify improvements in data architecture, pipeline performance, and engineering practices.
• Leverage Large Language Models (LLMs) and AI-assisted development tools to improve engineering productivity and accelerate delivery.
• Build solutions that are production-ready, scalable, and resilient while maintaining high development velocity.

Technical Skills

• Expert-level proficiency in SQL, including complex query optimization, performance tuning, and advanced data modeling.
• Strong expertise in data warehousing concepts, dimensional modeling, and analytical database design.
• Hands-on experience with modern data transformation frameworks such as:
  
• dbt
• SQLMesh
• Strong understanding of workflow orchestration, DAG design, dependency management, and data lineage.
• Experience designing and maintaining reliable, production-grade data pipelines.
• Strong knowledge of data quality frameworks, testing, validation, and monitoring.
• Excellent systems thinking with the ability to design scalable and maintainable data architectures.
• Proven ability to deliver high-quality solutions in fast-paced, agile environments.

AI & LLM Skills (Mandatory)

Demonstrated hands-on experience using Large Language Models (LLMs) as a core part of the software development lifecycle, including:

• Prompt engineering
• Context engineering
• Retrieval-Augmented Generation (RAG)
• Vector embeddings and vector search
• Token optimization and context management
• LLM evaluations and quality assessmentGuardrails and hallucination mitigation