Software Development Engineer 2

Role Summary

We are seeking a Data Engineer / Data Migration / Integration Engineer to help build, develop, and support scalable data platforms, migration solutions, and integration frameworks. These systems enable business-critical analytics, operational processes, and AI-powered capabilities. In this role you will work alongside senior engineers, growing your skills across data engineering, integration engineering, and cloud technologies.

Key Responsibilities

• Develop, test, and deploy data pipelines using Python, Java, and PySpark, with guidance from senior engineers.
• Support batch and micro-batch data processing solutions, and gain exposure to real-time processing.
• Contribute to ETL/ELT frameworks and reusable integration components.
• Assist with data migration and modernization initiatives across cloud and hybrid environments.
• Support and maintain REST API, event-driven, and Kafka-based integrations.
• Work with AWS and Azure data services to build and operate cloud-native data solutions.
• Apply data quality, monitoring, and governance practices, and help troubleshoot and resolve pipeline issues.
• Write clear technical documentation and participate in code reviews, design discussions, and team knowledge sharing.
• Help build secure, reliable data foundations that power analytics and AI-enabled products.

Technical Skills & Qualifications

Required Qualifications

• Bachelor's degree in Computer Science, Engineering, Information Systems, or a related field.
• 4 + years of experience in Data Engineering, Data Migration, Integration Engineering, or related roles (strong internship or project experience considered).
• Solid programming skills in Python, Java, and SQL.
• Hands-on experience with PySpark and Spark SQL, and an understanding of distributed data processing concepts.
• Working knowledge of Databricks or a similar big-data platform.
• Exposure to AWS and/or Azure data services.
• Understanding of ETL/ELT concepts, data modeling basics, and relational databases.
• Familiarity with REST APIs, Git/GitHub, and CI/CD fundamentals.

Preferred Qualifications

• Exposure to Snowflake, Delta Lake, Airflow, Kafka, SnapLogic, ADLS, or SQL Server.
• Familiarity with Salesforce (SFDC) or Microsoft Dynamics 365 (D365).
• Basic experience with workflow orchestration tools such as Airflow or Tidal.
• Scala knowledge.
• Interest in AI and Generative AI, and in using AI tools to improve developer productivity.

Core Technology Stack

Python, Java, SQL, PySpark, Spark SQL, Databricks, Snowflake, Airflow or Tidal, Kafka, REST APIs, AWS, Azure, GitHub, Delta Lake, SnapLogic, ADLS, SQL Server, AI-assisted Development

AI & Future-Ready Engineering Expectations

• Use AI-assisted development tools to speed up coding, testing, debugging, and documentation.
• Review and validate AI-generated outputs for correctness, security, and maintainability, seeking guidance from senior engineers as needed.
• Build foundational understanding of LLMs, Retrieval-Augmented Generation (RAG), embeddings, and AI data pipelines.
• Follow responsible AI practices and team standards.

Success Indicators

• Deliver accurate, well-tested work on assigned tasks with limited rework.
• Own small to medium-sized tasks and features from development through deployment, with support from senior team members.
• Learn quickly and steadily build independence in technical design and troubleshooting.
• Contribute to improvements in automation, reliability, and operational efficiency.
• Communicate progress, risks, and blockers clearly and on time.