Senior Data & Analytics Engineer

In this role you will:

• 100% hands-on role to build a robust and scalable data platform to support seamless data onboarding and management for a SaaS platform.
• Design scalable single-tenant and multi-tenant SaaS data platforms, optimize materialized views for analytics, and develop pipelines using the AWS Data Engineering stack.
• Design and implement efficient data migration scripts and workflows to enable smooth data onboarding for new and existing clients.
• Write clean, efficient code in Python, Java, or Go, and design robust data models using Postgres ORM frameworks.
• Process large-scale datasets, optimize Postgres databases for high performance, and implement best practices for scaling analytics solutions.
• Index optimization in Postgres for query performance.
• Creating materialized views and analytics-ready datasets for headless BI.
• Implement row-level security and design multi-tenant database architectures for scalability and security.
• Develop pipelines and processes to integrate diverse data connectors into the SaaS platform while ensuring data integrity and consistency.
• Enable data accessibility and transformation for data science teams by creating analytics-ready datasets and facilitating model integration.
• Ensure the data platform and migration workflows are optimized for scalability, high performance, and low latency.
• Work closely with product, engineering, and data science teams to align platform capabilities with analytics and machine learning requirements.
• Manage and scale AWS infrastructure and automate workflows using the GitHub DevOps stack.

You should have:

• Bachelor’s degree in STEM field.
• At least 5 to 8 years of extensive experience as a Data and Analytics engineer building data platforms for SaaS apps, large-scale data processing workflows, advanced analytics and processing techniques.
• Experience in database migration projects.
• Experience in build or migration of multi-tenant database projects.
• Deep competence in Python scripting for writing ETL pipelines, custom migration scripts, and automating AWS tasks.
• Deep competence in Java/Go for building high-performance, scalable tools to handle complex migration needs.
• Deep competence  in data storage and management using AWS RDS(postgres), S3 and Document DB.
• Deep competence of Postgres database architecture and functionality, including indexes, partitioning, and query optimization.
• Deep competence  in Materialized Views, including their creation, refresh strategies, and use cases for analytics.
• Advanced SQL skills to design complex queries that aggregate, filter, and transform data effectively for materialized views.
• Deep competence in data processing using AWS Glue, Lambda and Step functions.
• Have experience in AWS data migration service.
• Deep competence in data processing and analytics using AWS Athena and AWS Redshift.
• Deep competence in security and monitoring using AWS IAM, AWS CloudWatch and AWS CloudTrail. 
• Experience in design mapping between MongoDB’s flexible schema and Postgres' relational schema.
• Experience in data enrichment and cleaning techniques. 
• Proven experience with scalable, large data sets and high-performance SaaS applications.
• Strong ability to work with and optimize large-scale data systems
• You are a data engineer with a strong background in building scalable analytics solutions in startup environments.
• You are passionate about creating efficient data processing systems and driving analytics innovation.
• You are a problem solver with excellent programming skills and a focus on performance optimization.
• You are a collaborative team player who enjoys mentoring peers and sharing best practices.

Even better if you are:

• Familiar with Rust programming language.
• An entrepreneurial problem solver comfortable in managing risk and ambiguity.