Description:
We are looking for a highly experienced Senior Data Engineer with strong presales and solution design capabilities, who can architect and deliver end-to-end data solutions across on-premises and cloud environments. The ideal candidate will play a key role in engaging with clients, understanding business requirements, and designing scalable, secure, and high-performance data platforms.
Key ResponsibilitiesPresales & Solution Design
- Engage with clients to understand business and technical requirements, and translate them into data architecture and solution designs
- Lead technical presales activities, including RFP responses, proposals, effort estimation, and solution presentations
- Design end-to-end data solutions covering ingestion, transformation, storage, and visualization
- Provide architecture guidance for hybrid environments (on-prem + cloud)
Data Engineering & Delivery
- Build and manage scalable ETL/ELT pipelines using modern data engineering tools and frameworks
- Design and implement data lakes, data warehouses, and lakehouse architectures
- Work with structured, semi-structured, and unstructured data across multiple platforms
- Ensure data quality, governance, and compliance standards are maintained
Cloud & Hybrid Architecture
- Architect and deploy data platforms on Azure, AWS, or GCP, integrated with on-prem systems
- Lead data migration and modernization initiatives from on-prem to cloud
- Optimize performance, cost, and reliability of data solutions
Stakeholder Management & Leadership
- Collaborate with business, engineering, and analytics teams to deliver impactful solutions
- Mentor junior engineers and review designs/code for quality and standards
- Act as a trusted advisor for clients on data strategy and technology roadmap
Required Skills & Qualifications
- Bachelor’s/Master’s degree in Computer Science, Engineering, or related field
- 7+ years of experience in data engineering and data architecture
- Hands-on expertise with cloud platforms (Azure/AWS/GCP) and hybrid environments
- Strong experience with Databricks / Spark / big data technologies
- Proficiency in Python, SQL, and data processing frameworks
- Experience with data integration tools (ADF, Airflow, etc.)
- Solid understanding of data modeling, warehousing, and ETL principles
- Exposure to presales, client interaction, and solution design