Senior Data Engineer

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



Being a consultant in our team is a fun, challenging, and rewarding career choice. Your contributions are highly valued by clients, and the work you do often has a direct and significant impact on their business.

You will have the opportunity to work on a variety of projects for our incredible clients, which will accelerate your career growth. You’ll collaborate with modern technologies and work alongside some of the best professionals in the industry!

If you’re eager to be part of an exciting, challenging, and rapidly growing consultancy, we encourage you to apply. #LI-Remote

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