What are the responsibilities and job description for the Snowflake Lead Data Engineer position at Anblicks?
Responsibilities
- Lead the end-to-end architecture and implementation of Snowflake(Bronze/Silver/Gold layers).
- Partner with business and data stakeholders to translate requirements into canonical models, ontologies, and data products.
- Define and enforce data modeling standards, naming conventions, and domain-driven design principles.
- Guide teams on data ingestion patterns, transformation frameworks (e.g., dbt), and performance optimization in Snowflake.
- Integrate data management capabilities including Data Quality using SODA, Data Governance, Metadata Management, and Data Observability.
- Ensure platform scalability, security, cost optimization, and compliance with enterprise standards.
- Provide technical leadership and mentorship to data engineers and modelers.
- Act as a key contributor in roadmap planning, technical decision-making, and stakeholder communication.
Required Skills & Experience
- 10 years of experience in data engineering and platform architecture, with at least 3 years in a lead role.
- Strong hands-on experience with Snowflake (performance tuning, clustering, security, cost optimization).
- Hands-on experience with cloud platforms (AWS, Azure, or GCP)
- Understanding with Data Domains (Client, Finance etc.)
- Deep understanding of data modeling (dimensional, canonical, domain-driven).
- Experience designing or working with ontology / semantic layers (business vocabularies, relationships, metrics).
- Strong knowledge of modern data stack tools (dbt, orchestration, CI/CD for data).
- Experience implementing Data Quality, Data Governance, Metadata, and Data Observability solutions.
- Experience with orchestration tools such as: Apache Airflow, Prefect, or Luigi.
- Solid SQL skills and strong understanding of ELT patterns.
- Ability to lead cross-functional teams and communicate complex concepts to both technical and non-technical stakeholders.
Nice to Have
- Experience with knowledge graphs, semantic models, or graph technologies.
- Exposure to enterprise data platforms supporting multiple domains and global users.
- Background in cloud-native architectures and large-scale data modernization programs.