Mongo Data Engineer

Job description

Must Have Technical/Functional Skills

Mandatory hands-on experience with MongoDB

• Designing schemas, writing complex queries, performing aggregations, and optimizing performance within MongoDB environments.
• Developing data patches and data migrations (including DDLs/DMLs) using Python scripts
• Understanding of NoSQL data modeling patterns and principles (e.g., document-oriented, key-value).
• Familiarity with other NoSQL database types and their use cases (e.g., Cassandra, DynamoDB, Redis) is a plus.

PL/SQL Proficiency (Mandatory)

• Extensive experience in developing, debugging, and optimizing complex stored procedures, functions, triggers, and packages using PL/SQL.
• Strong understanding of relational database concepts, including normalization, indexing, and referential integrity.
• Experience with a major relational database system (e.g., Oracle, PostgreSQL, SQL Server).
• Data Platforms

Snowflake (Must Have)

• Strong experience with Snowflake Data Cloud development, including DDL/DML, stored procedures, UDFs, and performance optimization within Snowflake.
• Understanding of Snowflake's architecture (compute, storage, cloud services) and features (e.g., Virtual Warehouses, Zero-Copy Clones, Time Travel, Streams, Tasks).
• Experience with data loading/unloading into and out of Snowflake.

Apache Iceberg (Preferred)

• Practical experience with Apache Iceberg for managing large, high-performance data sets in open table formats.
• Understanding of Iceberg's key features, such as schema evolution, hidden partitioning, time travel, and manifest files.
• Experience integrating Iceberg with query engines (e.g., Spark, Presto, Trino) or data lakes.
• Performance Tuning (Must Have)
• Proven ability to diagnose and resolve database performance issues across relational and NoSQL environments.
• Expertise in query optimization (e.g., analyzing execution plans, rewriting inefficient queries).
• Experience with index tuning, partitioning strategies, and database configuration for optimal performance.
• Familiarity with database monitoring tools and techniques.
• Programming and Scripting

Python (Must Have)

• Experience with Python for database automation, scripting, data processing, and API integrations.
• Familiarity with relevant Python libraries for database connectivity (e.g., psycopg2, pymongo,
• snowflake-connector-python). Roles & Responsibilities
• Work on DB design, development and migration for complex high volume applications in financial domain
• Work on writing ETL/ELT pipelines and scripts
• Work on data modelling and developing real time data processing capabilities
• Query performance tuning and optimization techniques
• Identify and troubleshoot DB issues based on feedback
• Track the project status, issues, risks and updates timely with senior leadership.
• Programming of software applications, Project management, Consulting techniques,
• Project management methods, Deadline management, Managing unexpected changes Salary Range: $90,000 to $110,000 per year </div

Qualifications

BACHELOR OF COMPUTER SCIENCE