Sr. Software Engineer - MS-SSIS

Experience

Job Description

SQL Languages: SSIS, MS-SQL, PL/SQL

ETL Tool: SQL Server Integration Services etc.

Reporting Tool: SQL Server Reporting Services

Task Control: Azure DevOps, JIRA

Required Technical/ Functional Competencies

Domain/ Industry Knowledge:

• Basic knowledge of customer's business processes- relevant technology platform or product.
• Able to prepare process maps, workflows, business cases and simple business models in line with customer requirements with assistance from SME and apply industry standards/ practices in implementation with guidance from experienced team members.

Requirement Gathering and Analysis:

• Working knowledge of requirement management processes and requirement analysis processes, tools & methodologies.

• Able to analyse the impact of change requested/ enhancement/ defect fix and identify dependencies or interrelationships among requirements & transition requirements for engagement.

Product/ Technology Knowledge:

• Working knowledge of technology product/platform standards and specifications.

• Able to implement code or configure/customize products and provide inputs in design and architecture adhering to industry standards/ practices in implementation.

• Analyze various frameworks/tools, review the code and provide feedback on improvement opportunities.

Architecture tools and frameworks:

• Working knowledge of architecture Industry tools & frameworks.

• Able to identify pros/ cons of available tools & frameworks in market and use those as per Customer requirement and explore new tools/ framework for implementation.

Architecture concepts and principles:

• Working knowledge of architectural elements, SDLC, methodologies.

• Able to provides architectural design/ documentation at an application or function capability level and implement architectural patterns in solution & engagements and communicates architecture direction to the business.

Analytics Solution Design:

• Knowledge of statistical & machine learning techniques like classification, linear regression modelling, clustering & decision trees.

• Able to identify the cause of errors and their potential solutions.

Tools & Platform Knowledge:

• Familiar with wide range of mainstream commercial & open-source data science/analytics software tools, their constraints, advantages, disadvantages, and areas of application.

Required Behavioral Competencies

Accountability: Takes responsibility for and ensures accuracy of own work, as well as the work and deadlines of the team.

Collaboration: Shares information within team, participates in team activities, asks questions to understand other points of view.

Agility: Demonstrates readiness for change, asking questions and determining how changes could impact own work.

Customer Focus: Identifies trends and patterns emerging from customer preferences and works towards customizing/ refining existing services to exceed customer needs and expectations.

Communication: Targets communications for the appropriate audience, clearly articulating and presenting his/her position or decision.

Drives Results: Sets realistic stretch goals for self & others to achieve and exceed defined goals/targets.

Resolves Conflict: Displays sensitivity in interactions and strives to understand others’ views and concerns.

Certifications