Data Integration Tech Leader

About the Team / Role

Work as part of a team dedicated to delivering customizable reporting and processing solutions for external stakeholders. Also, this role involves maintaining and supporting legacy code while contributing to the design and implementation of data platform modernization initiatives.

How you'll make an impact :

Support applications both during and outside business hours.

Research issues and Service Requests quickly and efficiently. Engage in discussions and propose solutions.

Support production deployments, which occur on evenings and weekends. Contribute to post-deployment application validation. Quickly troubleshoot, evaluate, and resolve any issues that arise.

Participate in and lead team meetings and feature discussions.

Create basic designs for new and existing features.

Develop solutions that can be performant, scalable, consistent, and supportable that can be accomplished within the available scope, time and budget.

Participate in code reviews within the team and across other teams to ensure implementations adhere to goals, standards, and best practices.

Deliver software that meets requirements by learning the product area to provide the best long-term solutions.

Write code that is testable at all levels (unit, integration, and end-to-end.) 50% hands on coding.

Assist in increasing unit test coverage.

Review requirements and provide meaningful and timely feedback to improve them.

Ask questions to ensure requirements are feasible, implementation is efficient, and the design is aligned with the technical direction set by your team and Architects.

Participate in estimation and prioritization of project requests.

Establish relationships with Architects, Software Engineers, Quality Assurance Engineers and Product Owners to collaborate on design and delivery decisions.

Contribute to the prioritization of performance improvements and technical debt.

Understand common security vulnerabilities and best practices defined by Architects to reduce risk of security threats.

Design and develop technical solutions in all environments, resulting in an increased level of throughput. Others use your code as an example to learn from.

Product Proficiency

Understand your team's product domain and act as an internal subject matter expert.

Basic knowledge of multiple product domains.

Able to discuss application behavior and technology outside of the Development department in both a technical and business communication style.

Help others complete tasks to accomplish goals; step into other roles to ensure project deadlines are met.

Serve as a mentor with an ability to onboard new Software Engineers ensuring they have the proper tools and knowledge to become productive quickly.

Participate in the interview process and provide valuable hiring recommendations.

Provide technical and domain guidance to internal and external team members.

Lead features or components through the full software deployment lifecycle, including integration, customer feedback, release, and support phases.

Recommend ways to distribute work across your team to increase development efficiency.

Perform effectively in a cross-functional team environment to ensure successful execution and delivery of project commitments.

Demonstrate expertise in a domain as evidenced by others seeking your peer reviews, advice, and problem-solving.

Communicate priorities and dependencies across teams to ensure successful execution and delivery of commitments.

Build relationships with Quality Assurance Engineers, Architects, Product Owners, Support, Management, Configuration Management, Database Administrators, etc.

• Design and implement robust, scalable data ingestion and transformation pipelines using both batch and streaming architectures.
• Develop and maintain data flows across Data Lake, Data Warehouse, and Analytics platforms.
• Collaborate with data analysts, data scientists, and business stakeholders to understand data needs and deliver end-to-end solutions.
• Work with structured and semi-structured data from diverse sources, ensuring data quality, consistency, and reliability.
• Optimize and modernize legacy data integration processes and contribute to data platform migration and modernization initiatives.
• Modernize legacy ETL workflows to cloud-native pipelines
• Cloud & Big Data Ecosystems : Microsoft Azure (Azure Data Factory, Azure Data Lake Gen2, Azure Synapse Analytics, Azure Databricks, Azure Event Hub); AWS (Glue, S3, Redshift)
• Apache Kafka for real-time data streaming
• Databricks for advanced data engineering and analytics
• Snowflake for cloud-native data warehousing
• ThoughtSpot for self-service analytics
• DEHUB for enterprise data hub architecture
• ETL / ELT & Legacy Stack : SQL Server Integration Services (SSIS); SQL Server Reporting Services (SSRS); T-SQL for stored procedures, functions, and performance tuning
• Strong knowledge of ETL / ELT patterns and data modeling best practices
• Other Skills : Proficiency in Python, PySpark; Familiarity with CI / CD practices and version control (e.g., Github; Knowledge of data governance, lineage, and metadata management tools is a bonus