Hiring DynamoDB Developers: The Complete Guide

What DynamoDB Developers Actually Do

"DynamoDB Developer" is usually a skill add-on rather than a standalone role:

Backend Developers with DynamoDB Skills

Most common need. These developers:

• Use DynamoDB as the database for serverless applications
• Design table schemas and access patterns
• Write queries using DynamoDB SDK (JavaScript, Python, Go, etc.)
• Implement single-table design patterns
• Optimize queries and indexes for performance

Common for AWS-native applications and serverless architectures.

Serverless / AWS Engineers

Focus on cloud-native applications:

• Build Lambda functions that interact with DynamoDB
• Design event-driven architectures with DynamoDB Streams
• Implement DynamoDB as part of serverless stacks
• Handle DynamoDB integration with other AWS services
• Optimize for cost and performance at scale

DynamoDB is central to many serverless architectures.

Database Engineers / Architects

Focus on data modeling:

• Design complex DynamoDB data models
• Optimize partition keys and sort keys
• Plan for scale and performance
• Handle migrations and data modeling patterns
• Choose between DynamoDB and other databases

Needed when DynamoDB is critical infrastructure at scale.

Skill Levels: What to Test For

Level 1: Basic DynamoDB (Every AWS Backend Dev)

• Create tables and understand basic concepts
• Perform basic CRUD operations (PutItem, GetItem, Query)
• Understand primary keys (partition key, sort key)
• Use DynamoDB SDK in their language
• Basic understanding of NoSQL vs SQL

Red flag: Never used DynamoDB or any NoSQL database

Level 2: Competent DynamoDB User

• Designs effective table schemas
• Writes efficient queries and scans
• Understands Global Secondary Indexes (GSI)
• Implements single-table design patterns
• Handles DynamoDB Streams and triggers

This is the minimum for backend developers using DynamoDB in production.

Level 3: DynamoDB Expert

• Designs complex single-table models
• Optimizes partition keys for even distribution
• Understands capacity modes (on-demand vs provisioned)
• Handles large-scale migrations and data modeling
• Knows when DynamoDB fits vs alternatives

This is Database Engineer or AWS Architect territory.

Common Use Cases and What to Look For

Serverless Applications

Lambda functions with DynamoDB backend:

• Priority skills: SDK usage, single-table design, event-driven patterns
• Interview signal: "How would you build a serverless API with DynamoDB?"
• Red flag: Tries to use DynamoDB like a relational database

High-Scale Web Applications

Applications requiring predictable performance:

• Priority skills: Partition key design, GSI optimization, capacity planning
• Interview signal: "How would you design DynamoDB for a high-traffic app?"
• Red flag: Doesn't understand hot partitions or scaling challenges

Mobile Backends

Mobile app data storage:

• Priority skills: SDK integration, offline sync patterns, data modeling
• Interview signal: "How would you store user data for a mobile app?"
• Red flag: No understanding of mobile-specific patterns

Gaming Applications

Game state and leaderboards:

• Priority skills: High-throughput writes, time-series patterns
• Interview signal: "How would you store game scores and leaderboards?"
• Red flag: Doesn't understand gaming-specific access patterns

IoT Data Ingestion

Time-series and sensor data:

• Priority skills: High write throughput, TTL, data partitioning
• Interview signal: "How would you store IoT sensor data?"
• Red flag: No understanding of time-series patterns

Common Hiring Mistakes

1. Testing Basic CRUD Only

Knowing how to PutItem/GetItem doesn't differentiate candidates. Test data modeling, query design, and understanding of DynamoDB's strengths/limitations.

2. Ignoring Single-Table Design Knowledge

DynamoDB's single-table design is a key differentiator. Many developers struggle with this pattern. Test their understanding of access pattern design.

3. Not Understanding Partition Key Design

Hot partitions are a common problem. Good candidates understand partition key design and even data distribution.

4. Overlooking Cost Awareness

DynamoDB pricing can be complex (on-demand vs provisioned, read/write units). Candidates should understand cost implications of their design choices.

5. Conflating DynamoDB with Relational Databases

DynamoDB requires different thinking than SQL databases. Candidates who try to normalize data or use complex joins will struggle.

Interview Approach

For Backend Developers (DynamoDB as Skill)

Focus on practical scenarios:

• "Design a DynamoDB table for [use case]"
• "How would you query this data efficiently?"
• "Explain single-table design vs multi-table"

For Database Engineers (DynamoDB as Focus)

Focus on advanced topics:

• "Design a complex data model with multiple access patterns"
• "How would you optimize for cost and performance?"
• "When would you use DynamoDB vs RDS vs other databases?"

Recruiter's Cheat Sheet

Questions That Reveal Skill Level

Resume Green Flags

• Specific DynamoDB features used (GSIs, Streams, TTL, on-demand mode)
• Production scale experience ("Managed DynamoDB tables with 1B+ items")
• Mentions single-table design or access pattern optimization
• Serverless/AWS architecture experience
• Cost optimization experience

Resume Red Flags

• Only lists "DynamoDB" without specifics
• No mention of data modeling or access patterns
• "Expert in DynamoDB" but treats it like SQL
• Claims DynamoDB expertise but only knows basic CRUD

DynamoDB Concepts to Understand

Tables, Items, and Attributes

• Table: Container for items (like a database table)
• Item: Collection of attributes (like a row)
• Attribute: Key-value pair (like a column)

Primary Keys

• Partition Key (PK): Determines which partition stores the item
• Sort Key (SK): Optional, determines item order within partition
• Composite Primary Key: PK + SK combination

Access Patterns

• Query: Efficient retrieval using partition key (and optionally sort key)
• Scan: Reads entire table (expensive, avoid when possible)
• GetItem: Retrieves single item by primary key

Indexes

• Local Secondary Index (LSI): Same partition key, different sort key
• Global Secondary Index (GSI): Different partition and sort keys
• Use for: Alternative access patterns without changing table structure

Capacity Modes

• On-Demand: Pay per request, auto-scaling
• Provisioned: Specify read/write capacity units, more cost control

Good DynamoDB developers understand these concepts deeply.

Single-Table Design

DynamoDB's single-table design is a key pattern:

Traditional Approach (Multi-Table)

• Separate tables for Users, Orders, Products
• Requires multiple queries or joins (not supported)

Single-Table Design

• One table with different item types
• Use partition/sort keys to model relationships
• Enables efficient queries with fewer round trips

Example Structure

PK: USER#123          SK: METADATA        → User profile
PK: USER#123          SK: ORDER#456      → User's order
PK: ORDER#456         SK: METADATA       → Order details
PK: ORDER#456         SK: ITEM#789       → Order items

Single-table design is challenging but enables efficient queries. Good DynamoDB developers understand this pattern.

When to Use DynamoDB

Good Fit

• Serverless applications (Lambda + DynamoDB)
• High-scale applications with predictable access patterns
• Applications requiring single-digit millisecond latency
• AWS-native architectures
• Simple data models with clear access patterns

Not a Good Fit

• Complex relational queries (joins, aggregations)
• Applications requiring ACID transactions across multiple items
• Complex analytical queries
• Applications with unpredictable access patterns
• Teams unfamiliar with NoSQL patterns

Good DynamoDB developers understand when DynamoDB fits and when alternatives are better.