Job Description

Overview

This is a hybrid role, with the expectation that time working will regularly take place inside and outside of a company office.

Seeking for a skilled Software engineer role to design, develop and optimize database solutions across multiple platforms including SQL Server, Netezza and Snowflake. Looking for a candidate with strong database engineering expertise, a solid understanding of data base modeling and ETL skills, and the ability to build scalable and high-performance solutions for our applications. Experience working in Agile teams. Knowledge in any data virtualization tool.

Responsibilities

Responsible for designing, building, and maintaining data platform that supports data integrations for Enterprise Data Warehouse, Operational Data Store or Data Marts etc. with appropriate data access, data security, data privacy and data governance.
Establish enterprise-scale data integration procedures, data pipelines and frameworks across the data development life cycle. Suggest and implement appropriate technologies to deliver resilient, scalable, and future-proof data solutions.
Create data ingestion pipelines in data warehouses and other large-scale data platforms.
Creating scheduled as well as trigger-based ingestion patterns using scheduling tools.
Design, Develop and maintain databases solutions using SQL server, Netezza and Snowflake.
Create performance optimized DDLs for any row-based or columnar databases such as Netezza database per Logical Data Model.
Performance tuning of complex data pipelines and SQL queries.
Performs impact analysis of proposed changes on existing architecture, capabilities, system priorities, and technology solutions.
Manage deliverables of developers, perform design reviews and coordinate release management activities.
Estimate and provide timelines for project activities. Identify, document, and communicate technical risks, issues and alternative solutions discovered during project.
Drive automation, identify inefficiencies, optimize processes and data flows, and recommend improvements.
Use agile engineering practices and various data development technologies to rapidly develop and implement efficient data products.
Collaborate with Product Owners to understand PI goals, PI planning, requirement clarification, and delivery coordination.
Technical support for production incidents and failures
Work with global technology teams across different time zones (primarily US) to deliver timely business value.
Use Jira to manage tasks, track the progress and work in Agile environment.
Contribute to CI/CD, Automation, and Azure DevOps for database development.
Participate in migration activities and cloud modernization initiatives.

Qualifications

Bachelor's Degree and 4 years of experience in Software application development and maintenance OR High School Diploma or GED and 8 years of experience in Software application development and maintenance

Preferred:

Functional Skills:

Team Player: Support peers, team, and department management.
Communication: Excellent verbal, written, and interpersonal communication skills.
Problem Solving: Excellent problem-solving skills, incident management, root cause analysis, and proactive solutions to improve quality.
Partnership and Collaboration: Develop and maintain partnership with business and IT stakeholders
Attention to Detail: Ensure accuracy and thoroughness in all tasks.

Technical/Business Skills:

Strong expertise in SQL Server (T-SQL, Stored Procedures, indexing, Performance tuning)
Hands-on experience in Netezza, DB2 (Querying, Performance tuning, ETL)
Familiarity with ETL tools (SSIS, Data stage or equivalent)
Experience working in Agile team with Jira for issue tracking and sprint planning.
Prior work experience in large scale migration project.
Experience in at least one scripting language. Python is preferred.
Exposure to CI/CD pipelines (Azure Dev Ops) for code deployment.
Strong knowledge of data architecture, data design patterns, modeling, and cloud data solutions (Snowflake)
Data Model: Expertise in Logical and Physical Data Model using Relational or Dimensional Modeling practices, high volume ETL/ELT processes.
Performance tuning of data pipelines and DB Objects to deliver optimal performance
Experience working in Financial Industry is a plus.
 
Data Engineering:

Experience in designing and building Data Warehouse and Data lakes. Good knowledge of data warehouse principles, and concepts.
Technical expertise working in large scale Data Warehousing applications and databases such as Oracle, Netezza, and SQL Server.
Experience with public cloud-based data platforms especially Snowflake and AWS.

Data integration skills:

Expertise in design and development of complex data pipelines
Solutions using any industry leading ETL tools such as SSIS and IBM Data Stage.

Expert in SQL - development experience in at least one scripting language (Python etc.), adept in tracing and resolving data integrity issues.