Senior Snowflake Developer

Aegistech; New York (NY); Hybrid; USD 120,000 - 180,000; Full time

Job summary

Aegistech seeks a Senior Snowflake Developer for a 1+ year contract, hybrid onsite in Midtown NYC (4 days/week). Local candidates only; no relocation. This role requires valid U.S. work authorization and W-2 employment with no third parties.

The candidate will design, build, and optimize enterprise Snowflake data solutions, manage ELT/ETL pipelines, and contribute to architecture decisions, governance, and platform strategy. Strong Python, SQL, and cloud skills are required.

Qualifications

• Extensive hands-on experience designing and building Snowflake data solutions.
• Proficient in ELT/ETL pipelines and dbt frameworks.
• Strong Python-based data processing and automation skills.

Responsibilities

• Design, develop and optimize Snowflake data solutions.
• Build and optimize ELT/ETL pipelines.
• Develop robust data models and transformation frameworks.
• Implement data quality controls and monitoring.
• Collaborate with stakeholders and provide technical leadership.
• Support modernization and migration initiatives to cloud platforms.

Skills

Snowflake

SQL

Python

Cloud platforms

Orchestration tools

Data quality & observability

Job description

Our client is seeking a Senior Snowflake Development consultant for a 1+ year contract. This position is hybrid, onsite in Midtown NYC 4 days a week. Local Candidates only/NO RELOCATION.

This role is not eligible for employer-sponsored work authorization (e.g., H-1B, OPT, CPT, etc.) or transfer. Candidates must have valid U.S. work authorization

Candidate must be our W-2 employee. No third parties, please.

Senior Snowflake Developer

Role Summary:

A Senior Snowflake Developer designs, builds, and optimizes enterprise-grade data solutions on Snowflake, enabling scalable analytics, reporting, and data-driven decision-making. This role blends hands-on engineering, architectural influence, and stakeholder engagement to deliver high-quality, governed, cloud-native data products.

Core Responsibilities:

Solution Design & Development:

• Design, develop, and maintain scalable data solutions within Snowflake.
• Build and optimize enterprise ELT/ETL pipelines supporting critical reporting and analytics workloads.
• Design and implement robust data models (dimensional, analytical, operational).
• Develop and maintain reusable transformation frameworks using dbt.
• Build Python-based data processing, automation, and integration solutions.
• Contribute to architecture decisions, technical design standards, and platform strategy.
• Support modernization and migration initiatives from legacy systems to cloud-based platforms.
• Develop ingestion and transformation processes across diverse source systems (APIs, databases, SaaS, streaming).
• Optimize Snowflake databases, queries, warehouses, and workloads for performance and cost efficiency.
• Ensure solutions are scalable, maintainable, and aligned with enterprise engineering standards.
• Implement data quality controls, validation frameworks, and monitoring capabilities.
• Troubleshoot and resolve complex production issues, including performance bottlenecks and pipeline failures.

Stakeholder Engagement:

• Partner directly with business stakeholders to translate requirements into technical solutions.
• Facilitate workshops, discovery sessions, and requirements gathering.
• Communicate effectively with technical and non-technical audiences.
• Build strong relationships across business, analytics, engineering, and governance teams.
• Provide technical leadership, mentoring, and guidance throughout project delivery.

Governance & Best Practice:

• Champion best practices in data engineering, modeling, Snowflake usage, and software development.
• Contribute to technical documentation, standards, and knowledge-sharing initiatives.
• Support code reviews, testing, CI/CD, and release activities.
• Ensure compliance with governance, security, privacy, and regulatory requirements.

Top Skills & Technologies:

• Snowflake (warehouses, tasks, streams, Snowpipe, performance tuning)
• SQL (advanced analytics, optimization, modeling)
• Python (automation, orchestration, data processing)
• Cloud platforms (AWS, Azure, or GCP)
• Orchestration tools (Airflow, Prefect, Dagster)
• Data quality & observability (Great Expectations, Monte Carlo, Soda)