Role & responsibilities Senior Data Engineer will be responsible for designing, implementing, and maintaining data solutions on the Microsoft Azure Data platform and SQL Server (SSIS, SSAS, UC4 Atomic)Collaborate with various stakeholders, and ensuring the efficient processing, storage, and retrieval of large volumes of dataTechnical Expertise and ResponsibilitiesDesign, build, and maintain scalable and reliable data pipelines.Should be able to design and build solutions in Azure data factory and Databricks to extract, transform and load data into different source and target systems.Should be able to design and build solutions in SSISShould be able to analyze and understand the existing data landscape and provide recommendations/innovative ideas for rearchitecting / optimizing / streamlining to bring efficiency and scalability.Must be able to collaborate and effectively communicate with onshore counterparts to address technical gaps, requirement challenges, and other complex scenarios.Monitor and troubleshoot data systems to ensure high performance and reliability.Should be highly analytical and detail-oriented with extensive familiarity with database management principles.Optimize data processes for speed and efficiency.Ensure the data architecture supports business requirements and data governance policies.Define and execute the data engineering strategy in alignment with the companys goals.Integrate data from various sources, ensuring data quality and consistency.Stay updated with emerging technologies and industry trends.Understand the big picture business process utilizing deep knowledge in banking industry and translate them to data requirements.Enabling and running data migrations across different databases and different serversPerform thorough testing and validation to support the accuracy of data transformations and data verification used in machine learning models.Analyze data and different systems to define data requirements. Should be well versed with Data Structures & algorithms.Define data mapping working along with business and digital team and data team.Data pipeline maintenance/testing/performance validationAssemble large, complex data sets that meet functional / non-functional business requirements.Analyze and identify gaps on data needs and work with business and IT to bring in alignment on data needs. Troubleshoot and resolve technical issues as they arise.Optimize data flow and collection for cross-functional teams.Work closely with Data counterparts at onshore, product owners, and business stakeholders to understand data needs and strategies.Collaborate with IT and DevOps teams to ensure data infrastructure aligns with overall IT architecture.Implement best practices for data security and privacy.Drive continuous improvement initiatives within the data engineering functionOptimize data flow and collection for cross-functional teams.Understand impact of data conversions as they pertain to servicing operations.Manage higher volume and more complex cases with accuracy and efficiency.Required Skill's: Design and develop warehouse solutions using Azure Synapse Analytics, ADLS, ADF, Databricks, Power BI, Azure Analysis ServicesShould be proficient in SSIS, SQL and Query optimization.Should have worked in onshore offshore model managing challenging scenarios. Expertise in working with large amounts of data (structured and unstructured), building data pipelines for ETL workloads and generate insights utilizing Data Science, Analytics.Expertise in Azure, AWS cloud services, and DevOps/CI/CD frameworks.Ability to work with ambiguity and vague requirements and transform them into deliverables.Good combination of technical and interpersonal skills with strong written and verbal communication; detail-oriented with the ability to work independently.Drive automation efforts across the data analytics team utilizing Infrastructure as Code (IaC) using Terraform, Configuration Management, and Continuous Integration (CI) / Continuous Delivery (CD) tools such as Jenkins.Help build define architecture frameworks, best practices & processes. Collaborate on Data warehouse architecture and technical design discussions.Expertise in Azure Data factory and should be familiar with building pipelines for ETL projects.Expertise in SQL knowledge and experience working with relational databases.Expertise in Python and ETL projectsExperience in data bricks will be of added advantage. Should have expertise in data life cycle, data ingestion, transformation, data loading, validation, and performance tuning.

Role & responsibilities:Research and interpret complex changes in federal and state tax laws, analyzing their implications for our tax products.Collaborate with developers to translate tax law changes into logical calculations.Mentor and manage a team of tax analysts, fostering their professional development and ensuring timely delivery of deliverables.Communicate effectively with US and Indian leadership teams, providing clear and concise updates on tax initiatives and progress.Develop and implement strategies to minimize delivery turn-around time, while maintaining quality.Prepare and review complex tax calculations and ensure maximum coverage for the tests.Stay current on the latest tax trends and developments through ongoing research and professional development activities.Required Skills:Strong understanding of US individual taxation and Form 1040.Proven ability to research and interpret complex tax laws.Excellent analytical and problem-solving skills.Strong numerical aptitude and attention to detail.Effective communication and interpersonal skills.Experience in mentoring and guiding team members.Proficiency in MS Office suite (Excel, Word, PowerPoint).Basic understanding of software development concepts. Preferred candidate profile Perks and benefits

Role & responsibilities: Owning chargebacks and representing cases end-to-end from informing the merchant, to gathering evidence, and disputing the chargeback through to resolution. Acting as the go-to person, coaching and educating small business owners on the dispute lifecycle. Identify proactive opportunities for the business to protect themselves against future disputes. Understanding the differences between card networks and being comfortable explaining them to customers. Juggling multiple priorities, shifting between support activities (like communicating with business owners via email/phone), building chargeback cases from the ground up, all while meeting operational deadlines. Analyzing and understanding insights into cases and interpreting those outcomes into ways to improve chargeback efficiency and reduce collections. Required Skills: 1- 2 years of related work experience. Extensive knowledge and experience with e-commerce card payments and ACH payments, ideally both in Canada and the United States. Solid experience handling chargebacks and dispute resolution, whether on the merchant or issuer side. Good understanding of Payment Card Network chargeback rules and regulations. Good understanding of NACHA and Payments Canada rules and regulations. Understanding of full credit card chargeback dispute life cycles. Excellent customer service, relations and/or vendor management skills Strong analytical and problem-solving skills.

Role & responsibilities: Lead Data Engineer will be responsible for designing, implementing, and maintaining data solutions on the Microsoft Azure Data platform (Databricks,Azure Data Factory, Python) Leading a team of data engineers, collaborating with various stakeholders, and ensuring the efficient processing, storage, and retrieval of large volumes of data Maintaining and enhancing the data pipelines necessary to support business operations, analytics workloads, reporting needs and insights the impact the strategic and tactical implementation for the organization. Should be able to consume business and functional requirements and translation them into technical implementations. This role will also be responsible for providing technical expertise and direction to their team to ensure quality, standards, processes, and methodologies are being followed and work through technical challenges the team may face. Technical Expertise and Responsibilities :Design, build, and maintain scalable and reliable data pipelines. Should be able to design and build solutions in Azure data factory and Databricks to extract, transform and load data into different source and target systems. Should be able to analyze and understand the existing data landscape and provide recommendations/innovative ideas for rearchitecting / optimizing / streamlining to bring efficiency and scalability. Must be able to collaborate and effectively communicate with onshore counterparts to address technical gaps, requirement challenges, and other complex scenarios. Monitor and troubleshoot data systems to ensure high performance and reliability. Should be highly analytical and detail-oriented with extensive familiarity with database management principles. Optimize data processes for speed and efficiency. Ensure the data architecture supports business requirements and data governance policies. Define and execute the data engineering strategy in alignment with the companys goals. Integrate data from various sources, ensuring data quality and consistency. Stay updated with emerging technologies and industry trends. Understand the big picture business process utilizing deep knowledge in banking industry and translate them to data requirements. Enabling and running data migrations across different databases and different servers Perform thorough testing and validation to support the accuracy of data transformations and data verification used in machine learning models. Analyze data and different systems to define data requirements. Should be well versed with Data Structures & algorithms. Define data mapping working along with business and digital team and data team.Data pipeline maintenance/testing/performance validation Assemble large, complex data sets that meet functional / non-functional business requirements. Analyze and identify gaps on data needs and work with business and IT to bring in alignment on data needs. Understand impact of data conversions as they pertain to servicing operations.o Manage higher volume and more complex cases with accuracy and efficiency. Leadership Responsibilities :Provide leadership and guidance to the data engineering team, including mentoring, coaching, and fostering a collaborative work environment. Support team members with troubleshooting and resolving complex technical issues and challenges. Provide technical expertise and direction in data engineering, guiding the team in selecting appropriate tools, technologies, and methodologies. Stay updated with the latest advancements in data engineering and ensure the team follows best practices and industry standards. Align coding standards, conduct code reviews to ensure proper code quality level. Identify and introduce quality assurance processes for data pipelines and workflows. Stay up to date on the latest process and IT advancements to automate and modernize data systems for storage for performance, efficiency and cost savings with a cloud centric focus. Act as main point of contact to other teams/contributors. Work with product and business teams to understand and translate business requirements in to technical solutions. Implement proper security measures and procedures to prevent unauthorized entry and/or data loss. Promotes honest and open communication throughout the credit union. Demonstrate behaviors that are consistent with the credit unions values, philosophies, and leadership characteristics. Perform other duties as assigned. Foster a culture of collaboration, innovation, and continuous improvement within the team. Optimize data flow and collection for cross-functional teams. Work closely with Data counterparts at onshore, product owners, and business stakeholders to understand data needs and strategies. Collaborate with IT and DevOps teams to ensure data infrastructure aligns with overall IT architecture. Drive continuous improvement initiatives within the data engineering function.Required Skills: 5+ years of experience supporting big data platforms (cloud) Exceptional analytical and conceptual thinking skills coupled with strong written and verbal communication skills and ability to solve problems quickly. Strong technical skills in data engineering, including proficiency in programming languages and technologies such (Databricks,Azure Data Factory, Python) Should be proficient in SQL and Query optimization. Technical expertise understanding database design development, data models, and techniques for data mining. Expertise in working with various data tools and technologies, such as ETL frameworks, data pipelines, and data warehousing solutions. Preferred Cloud computing experience with preference for Microsoft Azure cloud technologies. Proven experience in leading a team of data engineers, providing guidance, mentorship, and technical support. In-depth knowledge of data management principles and best practices, including data governance, data quality, and data integration. Excellent interpersonal skills, with the ability to effectively collaborate with cross-functional teams, stakeholders, and senior management.• Drive automation efforts across the data analytics team utilizing Infrastructure as Code (IaC) using Terraform, Configuration Management, and Continuous Integration (CI) / Continuous Delivery (CD) tools such as Jenkins. Experience designing for data engineering models. Able to communicate effectively, both written and orally, with internal and external customers, vendors, and partners. Thrives in ambiguous technology situations. Ability to solve problems efficiently, think analytically, creatively, and logically. Ability to interact effectively with co-workers to accomplish daily tasks and to resolve interpersonal conflicts and miscommunications. Must be able to be bonded. Ability to maintain a high level of confidentiality. Should have experience as a technical lead mentoring data engineer and driving data-oriented projects. Should have worked in onshore offshore model managing challenging scenarios. Lead data architecture and implementation efforts to structure, integrate, govern, store, describe, model, and maintain data warehouse for optimal accuracy and usage. Ability to work with ambiguity and vague requirements and transform them into deliverables. Help build define architecture frameworks, best practices & processes. Collaborate on Data warehouse architecture and technical design discussions. Should have expertise in data life cycle, data ingestion, transformation, data loading, validation, and performance tuning

Role & responsibilities: Responsible for assisting team efforts to perform and automate application security testing and tools. Collaborate with development teams in identifying and building solutions to secure code. Perform periodic secure coding assessments & reviews to assess security vulnerabilities & identify the best way to reduce information security risks. Possess the ability to discuss and present technical solutions to all levels of the business. Facilitate development group discussions on vulnerability mitigation, good coding practices, and security risks. Contribute to the maintenance of static and dynamic code analysis tools. Identify new requirements / enhancements to standards, tools, and processes. Periodically, conduct developer training on Application Security concepts. A willingness to learn new tools and techniques on the fly. Required Skills: Masters in Information Security Practical knowledge of web application security testing. Understanding of web application security testing tools Understanding of OWASP Top 10 and CVE/SANS Top 25 Understanding of code scanning tools for SAST/DAST/SCA