Backend / Data Infrastructure Engineer

Employment: Full-time
Work Format: Remote

About the Company

We are a technology startup operating in the Data Infrastructure and Cloud Analytics domain. We are developing a platform that helps companies optimize analytical query execution by automatically selecting the most efficient database or query engine based on speed, cost, and performance.

Our product brings together modern database technologies, cloud platforms, and distributed systems to make large-scale data processing faster and more efficient.

About the Role

We are looking for a Backend / Data Infrastructure Engineer to join the development of our product's core architecture.

You will work at the intersection of Backend Development, Database Technologies, and Distributed Systems, building solutions that integrate different data processing systems and optimize analytical query execution.

This role is a good fit for an engineer who is interested not only in traditional data processing workflows but also in database internals, query architecture, and distributed infrastructure.

Key Responsibilities

• Develop and maintain backend services and APIs for interacting with different databases and query engines.
• Build and improve integrations with Snowflake, DuckDB, Trino, ClickHouse, BigQuery, and other systems.
• Develop mechanisms for SQL query routing, execution, and optimization across different query engines.
• Work with SQL parsing, logical query plans, and SQL dialect transformations.
• Ensure data consistency and result accuracy when executing queries across different systems.
• Work with data storage technologies, including Apache Iceberg.
• Develop automated benchmarking tools to test and compare different query engines in terms of execution speed, throughput, and cost.
• Improve the platform's reliability, scalability, and performance.

Requirements

• Practical experience in Software Engineering or Backend Development.
• Commercial development experience with Python; experience with Rust is also a plus.
• Experience working with databases, data warehouses, or analytical platforms.
• Understanding of SQL and database architecture.
• Hands-on experience with distributed systems.
• Understanding of SQL query optimization principles and database performance tuning.
• Understanding of ETL processes and data modeling.
• Experience developing APIs, integrations, or connectors for working with different systems.

Nice to Have

• Experience with Snowflake, BigQuery, Databricks, DuckDB, Trino, or ClickHouse.
• Experience with SQLGlot, Apache Calcite, Substrait, or SQL parsers.
• Understanding of Query Federation, Query Routing, and Query Pushdown.
• Experience with JDBC/ODBC, database connectors, or data migration between different systems.
• Knowledge of Apache Iceberg, Delta Lake, or Apache Hudi.
• Experience with data consistency validation and cross-database result comparison.
• Contributions to open-source projects in the Data Infrastructure domain.
• Experience working in early-stage startups.