Senior Cloud Data Engineer

Job Description

Dignep Group Pvt. Ltd. is a technology solutions company that combines cutting-edge innovation with deep understanding of people and processes to deliver impactful digital products. We partner with startups scaling their vision and enterprises evolving their capabilities building software the startup way. Our offerings span bespoke software development, dedicated teams, staff augmentation, and AI-powered solutions.

PURPOSE

The Senior Cloud Data Engineer will design, build, and maintain scalable cloud data platforms that power Dignep's internal analytics and client-facing data solutions. This role is central to enabling data-driven product development and delivering enterprise-grade data engineering services to our clients. You will architect and implement modern data ecosystems including data warehouses, lakes, and AI/ML pipelines that accelerate digital transformation for startups and enterprises alike.

TECHNICAL SKILLS

Cloud Data Engineering

• Enterprise-level experience in cloud data architecture covering data warehouses, data lakes, data marts, and operational data stores
• Expertise in batch and real-time data ingestion using Azure Data Factory (ADF), Snowflake, AWS Glue, or Informatica IICS
• Hands-on skills building, deploying, and monitoring scalable ETL/ELT pipelines within the Azure ecosystem

Azure Ecosystem

• Deep proficiency in Azure Data Lake, Azure Synapse Analytics, Azure SQL Database, Azure Blob Storage, and Azure ML
• Experience designing ADF pipelines, data flows, and integration runtimes for reliable, cost-optimized data ingestion
• Ability to integrate data pipelines with AI/ML workflows using ADF, Azure ML, Databricks, or Synapse ML

Data Integration & APIs

• Experience ingesting data from diverse sources: marketing platforms (Meta Ads, Google Ads, GA4), CRMs (Salesforce), analytics tools (BigQuery), REST APIs, sFTP, and file-based systems
• Skilled in troubleshooting pipelines, implementing triggers, automated alerts, and performance tuning

Data Modeling & Quality

• Strong knowledge of conceptual, logical, and physical data modeling for transactional and analytical systems
• Practical experience with normalization, denormalization, and tools like ER/Studio, Erwin, or SQL Power Architect
• Ability to design and maintain data quality frameworks, including profiling, validation, and cleansing strategies

Engineering Practices

• Advanced SQL for querying, managing, and optimizing cloud databases
• Solid CI/CD experience: branching strategies, Git version control, automated deployments
• Demonstrated ability to enforce coding standards, conduct code reviews, and lead testing (unit, integration, regression)

Governance & Compliance

• Experience establishing data standards, naming conventions, metadata management, and data lineage practices
• Familiarity with regulatory and contractual compliance requirements relevant to client engagements

EXPERIENCE & REQUIREMENTS

Area

Experience: 8–10 years in cloud data engineering, covering cloud data warehousing and data lakes, ETL/ELT pipeline development, SQL and data modeling (conceptual/logical/physical), Azure stack (Data Factory, Synapse, Databricks, Azure SQL, Data Lake/Delta Lake), data governance (MDM, metadata, data lineage, data quality), and exposure to AI/ML data pipelines.

-Must be able to work within US time zones

INTERPERSONAL & LEADERSHIP SKILLS

• Outstanding written and verbal communication skills; ability to build rapport quickly with clients, leadership, and cross-functional teams
• Proven collaboration across diverse, fast-moving teams in a startup-paced environment
• Ability to conduct detailed requirements gathering and translate client objectives into actionable technical plans
• Strong ownership mindset guiding stakeholders through complex processes with clear communication
• Experience mentoring and coaching team members, supporting their professional growth
• Comfortable presenting complex technical concepts to both technical and non-technical audiences

Location: Pulchowk Lalitpur

Reports To: Head of Engineering / CTO

Employment Type: Full-time