Senior Data Engineer

This is a fully remote position, open to applicants in Philippines.

📋 Description

• Design, construct, and maintain scalable and secure cloud-native data platforms and data pipelines.

• Lead the architecture, optimization, and operational oversight of the Snowflake data warehouse platform.

• Develop robust ELT/ETL pipelines to ingest, transform, and deliver high-quality data from various internal and external sources.

• Create reusable and maintainable data frameworks, transformation models, and orchestration workflows.

• Develop and sustain infrastructure-as-code and automation for data platform provisioning and management as appropriate.

• Optimize performance, scalability, and cost efficiency across data storage, transformation, and query workloads.

• Support near real-time and batch processing requirements for data.

• Assume ownership of and continuously enhance Snowflake architecture, performance tuning, security, governance, and operational best practices.

• Design and optimize Snowflake schemas, warehouses, clustering strategies, and data sharing capabilities.

• Implement scalable data modeling approaches, including dimensional modeling and data vault methodologies as applicable.

• Manage Snowflake access controls, roles, permissions, and secure data sharing practices.

• Monitor Snowflake usage, query performance, and cost consumption to drive optimization efforts.

• Support data lifecycle management, retention, and governance policies within Snowflake.

• Design and maintain curated, trusted, and scalable data models to support analytics, reporting, and operational use cases.

• Collaborate with analysts, business stakeholders, and engineering teams to translate business requirements into scalable data solutions.

• Enable self-service analytics capabilities through well-structured semantic layers and governed datasets.

• Support and optimize BI and reporting platforms such as Looker, Power BI, or similar tools.

• Ensure data structures and models cater to both operational reporting and strategic analytics needs.

• Implement data quality controls, validation frameworks, reconciliation processes, and monitoring capabilities.

• Proactively identify and resolve data integrity, consistency, and performance challenges.

• Establish observability and operational monitoring for data pipelines and platform reliability.

• Contribute to data governance, lineage, cataloging, and metadata management practices.

• Ensure that data platforms and engineering processes adhere to security, privacy, and regulatory requirements.

• Collaborate closely with Product, Engineering, Operations, Finance, and Business stakeholders to deliver impactful data solutions.

• Mentor and support junior engineers and analysts within the broader data function.

• Contribute to data engineering standards, best practices, and platform strategy.

• Drive continuous improvement initiatives across data architecture, tooling, and delivery practices.

• Work cross-functionally to enhance organizational data literacy and data maturity.

⛳️ Requirements

• Over 5 years of experience in Data Engineering, Analytics Engineering, or related roles on data platforms.

• Experience in designing and supporting multi-region and enterprise-scale data platform architectures.

• Strong background in driving performance optimization and cloud cost efficiency initiatives across large-scale data workloads.

• Solid understanding of platform reliability, operational maturity, resilience, and production support practices.

• Experience in implementing advanced governance, security, access control, and data protection models within enterprise data platforms.

• Strong capability in developing architectural standards, engineering documentation, and scalable platform design patterns.

• Proven hands-on expertise with Snowflake in enterprise-scale environments.

• Advanced SQL skills with a track record of optimizing complex analytical queries and data transformations.

• Extensive experience in building and maintaining modern ELT/ETL pipelines and orchestration workflows.

• Strong understanding of contemporary data warehousing concepts, dimensional modeling, and scalable data architecture.

• Experience with cloud platforms such as AWS, Azure, or GCP.

• Experience with data transformation and orchestration tools like dbt, Airflow, Fivetran, Matillion, or similar platforms.

• Proficient in integrating structured and semi-structured data sources.

• Strong grasp of data governance, security, and access management principles.

• Proven ability to manage large and complex datasets in production settings.

• Excellent analytical, troubleshooting, and problem-solving skills.

• Outstanding communication and stakeholder engagement abilities.

• Capability to work effectively in fast-paced, agile, and collaborative environments.

🏝️ Benefits

• Flexibility in work hours and location, emphasizing energy management over time management.

• Access to online learning platforms along with a budget for professional development.

• A collaborative, no-silos environment that promotes learning and growth across teams.

• A vibrant social culture featuring team lunches, social events, and opportunities for creative input.

• Health insurance coverage.

• Leave benefits.

• 13th Month Salary.