What we are looking for
- Education & Experience
- Education: Bachelor’s degree in Computer Science, Information Technology, Data Engineering, or a related field (or equivalent professional experience).
- Core Experience: Proven experience developing end-to-end data pipelines extracting/transforming/loading data from REST APIs, relational databases, cloud storage, and flat files.
- Snowflake Proficiency: Demonstrated hands-on experience with virtual warehouses, streams, tasks, stages, Snowpipe, secure data sharing, and performance optimization.
- SQL: Advanced SQL development skills with the ability to write complex queries, tune performance, and optimize large-scale workloads.
- Data Modeling: Experience with dimensional modeling techniques (star schemas, fact tables, dimension tables).
- Cloud & DevOps:
- Familiarity with cloud-based data ecosystems, particularly Microsoft Azure.
- Managing source code and CI/CD pipelines using Git and Azure DevOps (or similar).
- Soft Skills & Practices:
- Strong analytical, problem-solving, and detail-oriented mindset.
- Excellent verbal and written communication skills; ability to collaborate in a fast-paced environment with evolving priorities.
- Knowledge of data integration best practices, data governance, and enterprise data management.
- Preferred / Nice-to-Have
- Certifications: SnowPro, Azure Data Engineer Associate, or equivalent cloud data platform certifications.
- Advanced Tech: Big data technologies, machine learning, data science platforms, or advanced analytics.
- BI Tools: Power BI, Tableau, or similar visualization platforms.
- Methodologies: Agile delivery frameworks and DevOps practices.
- Preferred Tech Stack Summary
- Core: Snowflake, Python/PySpark, SQL
- Cloud & Orchestration: Azure Data Lake Storage (ADLS), Azure Data Factory, Azure Key Vault
- DevOps & Infrastructure: Git, Azure DevOps, CI/CD, Infrastructure as Code (Terraform preferred)
- Integration & Analytics: REST APIs, Power BI
Responsibilities
- Data Engineering & ETL Development
- Design, develop, and maintain scalable ETL/ELT pipelines using Python (PySpark), Snowflake, and cloud-native technologies.
- Build reliable, efficient, and reusable data ingestion, transformation, and loading processes.
- Snowflake Data Platform & Warehousing
- Utilize Snowflake’s architecture to design, build, and optimize modern cloud data solutions.
- Implement and manage Snowflake objects (databases, schemas, tables, views, streams, tasks, stages, stored procedures).
- Leverage virtual warehouses, data sharing, time travel, and automated scaling to balance performance and cost efficiency.
- Apply dimensional modeling (star schemas, facts, dimensions) to build scalable enterprise data warehouses.
- Data Integration & Modeling
- Extract and ingest structured and semi-structured data from REST APIs, relational databases, SaaS apps, flat files, and cloud storage.
- Develop robust ingestion frameworks.
- Collaborate with data architects and stakeholders to create logical and physical data models aligned with business goals.
- Cloud Architecture & Standards
- Contribute to modern data platform concepts (data lakes, lakehouses, data mesh architectures, enterprise data catalogs).
- Support integration between Snowflake and cloud-native services (primarily Azure).
- Establish and enforce data engineering standards and best practices.
- Quality, Governance & Security
- Implement automated data quality controls, validation frameworks, and monitoring processes.
- Support data governance initiatives and maintain adherence to organizational standards.
- Ensure data security, privacy, and regulatory compliance (access controls, masking policies, industry best practices).
- Optimization, Operations & Maintenance
- Monitor and optimize Snowflake workloads, ETL/ELT processes, and SQL queries to meet SLAs.
- Analyze warehouse utilization and recommend performance and cost-efficiency improvements.
- Monitor pipelines, diagnose performance issues, and implement long-term solutions; support production environments and incident resolution.
- Maintain comprehensive documentation for pipelines, flows, transformations, data models, and operational processes.
- Collaboration
- Partner with cross-functional teams (data architects, data scientists, analysts, business stakeholders) to understand requirements and provide technical expertise.
Company Benefits
- Competitive salary and bonuses, including performance-based salary increases.
- Generous paid-time-off policy
- Flexible working hours
- Work remotely
- Continuing education, training, conferences
- Company-sponsored coursework, exams, and certifications
Skills Required
- Bachelor's degree in Computer Science, IT, Data Engineering, or equivalent experience
- Proven experience developing end-to-end data pipelines (ETL/ELT) from REST APIs, relational databases, cloud storage, and flat files
- Hands-on experience with Snowflake (virtual warehouses, streams, tasks, stages, Snowpipe, secure data sharing, performance optimization)
- Advanced SQL development skills, query tuning, and large-scale workload optimization
- Experience with dimensional modeling (star schemas, fact and dimension tables)
- Familiarity with cloud-based data ecosystems, primarily Microsoft Azure
- Source control and CI/CD experience using Git and Azure DevOps (or similar)
- Strong analytical, problem-solving, communication skills, and knowledge of data governance and enterprise data management
- SnowPro, Azure Data Engineer Associate, or equivalent cloud data certifications
- Experience with big data technologies, machine learning, or advanced analytics
- Experience with BI tools such as Power BI or Tableau
- Experience with Infrastructure as Code (Terraform preferred) and DevOps practices
What We Do
Helping companies to disrupt in the cloud by providing: - Nearshore Staffing - Cloud consulting - Cloud migration strategies - Cloud native development Process Management and Improvement: Define a working methodology according to the best practices of development to fulfill customer needs. Champion ongoing processes and initiatives to implement the best practices of project management. Research about the latests technologies which could be applied to a project in order to innovate and satisfy project needs Team Building & Management: Empowering teams to ensure every member participation and engagement to the project. Ensure every member is proactively contributing to the progress of the project. Contribute and encourage the team to always provide velocity and quality for every deliverable.





