Data Engineer

Key Responsibilities
Design, develop, and support enterprise-scale data engineering solutions and scalable data pipelines
Build and optimize large-scale data processing solutions using SQL, Python, PySpark, and Spark
Develop and maintain modern data platform solutions using Snowflake, dbt, Kafka, Airflow, Iceberg, and Lakehouse architectures
Design and implement cloud-native data solutions using AWS services such as EMR, Glue, Athena, Lambda, DynamoDB, EC2, IAM, CloudFormation, and CloudWatch
Apply data architecture and modeling principles, including dimensional modeling, Data Vault, data warehousing, data governance, and master data management
Design and implement data streaming and distributed data processing solutions
Evaluate technical approaches and clearly communicate architecture decisions, implementation strategies, challenges, and outcomes
Lead technical initiatives and collaborate with engineering teams to deliver scalable data solutions
Gather business requirements and translate complex business needs into technical designs and solutions
Collaborate with business stakeholders and technical teams throughout the development lifecycle
Apply AI-assisted development tools, automation frameworks, and emerging technologies to improve engineering productivity, software quality, and delivery
Continuously evaluate and adopt modern engineering practices and technologies that improve data platform capabilities
Support CI/CD and DevOps practices for data engineering solutions
Troubleshoot performance, reliability, and data quality issues across data pipelines and platforms
Required Qualifications
5+ years of experience
Good to Have
AWS Solutions Architect
AWS Developer
AWS Data Analytics
Skills
SQL
Python
PySpark
AWS Cloud Services
Snowflake
dbt
Kafka
Airflow
Iceberg And Lakehouse Architectures
Data Pipeline Development
Data Streaming And Distributed Data Processing
Relational, NoSQL, And Graph Databases
Networking, Virtualization, And Distributed Systems
Data Architecture And Modeling
Technical Leadership
Requirements Gathering
Stakeholder Management
AI-Assisted Development
Troubleshooting And Data Quality
CI/CD And DevOps Practices
Linux Administration And Scripting
Agile Delivery
Distributed Team Collaboration
Schedule
Start date: 2026-10-07