Job Openings at Interswitch

Job Purpose

• Plans and implements pursuit of strategic opportunities for a particular business or organization, for example, by cultivating partnerships or other commercial relationships, or identifying new markets for its products or services.

Responsibilities

• Create a business development plan to identify, evaluate, and structure key transactions to ensure continued financial health and maximum value creation through the entire product life cycle. These transactions may involve alliances, collaborations, mergers and acquisitions, in and out licensing initiatives, and other activities.
• Develop and implement relationship management plans for complex potential customer accounts to identify and build relationships with relevant decision makers and influencers within the customer organization and to enable effective two-way flow of information and resolution of issues.
• Set clear objectives for each sales call or meeting; tailor standard materials to make presentations to decision makers and influencers within the customer organization; and ask relevant questions to gather information, to evaluate the customer's level of interest, and to identify and respond to areas requiring further information or explanation.
• Develop a personal network within the sales territory and represent the organization at trade shows and other events to identify sales opportunities, promote the organization, and enhance its reputation.
• Use personal expertise to identify the complex standard products and/or services offered by the organization that meet the customer's needs, together with quantities and product configurations. Present these to the customer with a clear rationale and at standard commercial terms, referring to senior colleagues where necessary to ask for concessions (e.g., price reduction) that gain the customer's agreement.
• Collaborate internally and work as the customer champion in cross-functional teams to build strong external customer relationships.
• Develop and implement a relationship management plan for existing customer accounts to identify and build relationships with relevant decision makers and influencers within the customer organization and to enable effective two-way flow of information and resolution of issues. Collect feedback from identified customers or customer segments to ensure their needs are met, providing themes, summary analyses, and recommendations for changes based on customer input.
• Enter customer information that has been gathered through research and/or through direct customer contact into the customer relationship management system, to ensure that the organization has quality data to enable effective customer retention and business development activities OR Ensure that team members maintain up-to-date customer relationship management data, identifying and resolving issues.
• Maintain and renew a deep knowledge and understanding of the organization's policies and procedures and of relevant regulatory codes and codes of conduct, and ensure own work adheres to required standards. OR Identify, within the team, patterns of non-compliance with the organization's policies and procedures, and with relevant regulatory codes and codes of conduct, taking appropriate action to report and resolve these and escalating issues as appropriate.
• Develop own capabilities by participating in assessment and development planning activities as well as formal and informal training and coaching; gain or maintain external professional accreditation where relevant to improve performance and fulfill personal potential. Maintain an in-depth understanding of technology, external regulation, and industry best practices through ongoing education, attending conferences, and reading specialist media.

Behavioral Competencies

• Builds strong customer relationships and delivers customer-centric solutions. For example, solicits customer feedback and data; conveys a clear understanding of the level of service the team is providing; takes action when standards are not met by team; aligns business process with customer needs.
• Relates openly and comfortably with diverse groups of people. For example, recognizes even subtle social cues and nimbly responds to others' needs and preferences. Helps to defuse difficult interpersonal situations by showing high levels of tact, sensitivity, and consideration. Builds rapport with ease.
• Makes sense of complex, high quantity, and sometimes contradictory information to effectively solve problems. For example, looks at complex issues from multiple angles; explores issues to uncover underlying issues and root causes; sees the main consequences and implications of different options.
• Develops and delivers multi-mode communications that convey a clear understanding of the unique needs of different audiences. For example, seeks out others' perspectives and asks good questions. Shares information that people want to know; gives appropriate context and details when speaking.
• Maneuvers comfortably through complex policy, process, and people-related organizational dynamics. For example, builds support for ideas among key decision makers and stakeholders. Anticipates political difficulties and identifies ways to overcome any resistance.
• Gains the confidence and trust of others through honesty, integrity, and authenticity. For example, demonstrates integrity, upholding professional codes of conduct. Instills trust by following through on agreements and commitments despite competing priorities and by being honest and straightforward
• Effectively builds formal and informal relationship networks inside and outside the organization. For example, engages with a wide network, across many functions, disciplines, and business units, to add value to organizational efforts. Leverages a wide network to provide insight and influence outcomes.

Skills

• Uses comprehensive knowledge and skills to act independently while guiding and training others to orient the seller's organization around delivering to the key needs of their customers.
• Keeps customer at center of sale, Collaborates with customers, Elevates partner insights, Uses common terminology.
• Uses comprehensive knowledge and skills to act independently while guiding and training others to propose a mutually agreed-upon agenda to start sales conversations that offer value to the client.
• Provides context for conversations, Proposes mutually valuable agenda, Leverages pre-call prep for partnerships, Confirms client understanding, Leverages pre-call prep, Adds value through perspective
• Uses comprehensive knowledge and skills to act independently while guiding and training others to accurately identify and understand the key buying influences pertaining to an opportunity.

Education

• Reputable University Degree (First degree)

Experience

• Experience enables job holder to deal with the majority of situations and to advise others (Over 6 years to 8 years).

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Job Purpose

• To build reliable data integration solutions, clean, transform, and analyze vast amounts of big data from various systems using Spark and other ETL tools to provide ready-to-use dataset to data scientists and data analysts, while ensuring data quality and integrity. Collaborate with stakeholders to design scalable and efficient data solutions that enable informed decision-making, and compliance with data governance.

Responsibilities

• Develop and implement efficient data ingestion pipelines to acquire and extract large volumes of structured and unstructured data. Ensure data integrity and quality during the ingestion process.
• Integrate various data sources and formats into a unified data ecosystem.
• Design and execute data processing workflows to clean, transform, and enrich raw data.
• Develop scalable data processing algorithms and techniques to handle big data volumes efficiently.
• Optimize data processing pipelines for performance and reliability.
• Document data engineering processes, workflows, and system architectures for future reference and knowledge transfer.
• Prepare technical documentation, including data dictionaries, data lineage, and system specifications.
• Create and maintain documentation related to data governance, compliance, and security protocols.
• Create and maintain data storage architectures that cater to the specific needs of big data applications. Implement robust data management strategies, including data partitioning, indexing, and compression techniques.
• Ensure data security, privacy, and compliance with relevant regulations.
• Collaborate with data scientists and analysts to understand their requirements and translate them into scalable data models.
• Apply data visualization techniques to communicate insights effectively.
• Create and maintain data storage architectures that cater to the specific needs of big data applications. Implement robust data management strategies, including data partitioning, indexing, and compression techniques.
• Ensure data security, privacy, and compliance with relevant regulations.
• Collaborate with data scientists and analysts to understand their requirements and translate them into scalable data models. Apply data visualization techniques to communicate insights effectively.
• Collaborate with cross-functional teams, including data scientists, analysts, and software engineers, to understand their data requirements and provide technical support.
• Communicate complex technical concepts and findings to non-technical stakeholders in a clear and concise manner.
• Participate in knowledge sharing activities and contribute to the continuous improvement of data engineering practices Identify and implement strategies to enhance the performance and efficiency of big data applications and systems. Conduct performance tuning, load testing, and capacity planning to meet scalability and throughput requirements.
• Monitor system performance and troubleshoot issues related to data processing, storage, and retrieval.
• Establish and enforce data governance policies, standards, and best practices.
• Ensure compliance with data regulations, such as GDPR or HIPAA, by implementing appropriate data protection measures.
• Conduct data audits and implement data quality controls to maintain data accuracy and consistency.

Behavioural Competencies

• Have strong analytical thinking skills to understand complex data requirements, identify patterns and trends in data, and design efficient and scalable data solutions. Be able to break down complex problems into manageable components and develop logical and effective solutions. Be able to analyze datarelated issues, troubleshoot problems, and implement appropriate resolutions.
• Approach challenges with a proactive mindset and come up with innovative and practical solutions.
• Have a keen eye for detail, ensuring data accuracy, quality, and integrity through thorough data validation and verification processes. Paying attention to performance optimization and data security measures.
• Be able to work effectively in a team environment, communicate and collaborate with team members (data scientists, analysts, software engineers, and other stakeholders), and contribute your expertise to achieve common goals
• Possess good communication skills to effectively communicate technical concepts and requirements to both technical and non-technical stakeholders.
• Be able to articulate your ideas, document your work, and create clear and concise technical documentation for future reference.
• Adhere to ethical guidelines and maintain a high level of professionalism.
• Prioritize data privacy, security, and compliance with relevant regulations.
• Demonstrate integrity, honesty, and accountability in your work.
• Stay updated with the latest trends and advancements in data engineering technologies, tools, and best practices. Actively seek opportunities for professional development and self-improvement.
• Anticipate potential issues, design robust and scalable data architectures, and implement monitoring and alerting systems to detect and address issues proactively.

Skills

• Proficiency in working with various Big Data technologies is essential. This includes Apache Hadoop, Apache Spark, Apache Kafka, Apache Hive, Apache Pig, and other related frameworks. Understand the architecture, components, and ecosystem of these technologies to design and implement robust data processing pipelines.
• Expertise in data processing and Extract, Transform, Load (ETL) techniques.
• Must be skilled in designing and implementing efficient data pipelines to extract data from various sources, transform it into a suitable format, and load it into target systems or data warehouses. Proficiency in PySpark and experience with Microsoft Azure Databrick is required.
• Proficiency in implementing CI/CD practices for data pipelines, including version control, automated testing, and deployment processes, using tools like Git, Jenkins, or similar platforms to ensure smooth and reliable deployment of data pipelines, for faster development cycles, improved code quality, and efficient release management.
• Proficiency in python programming language and SQL, to manipulate and transform data, build data pipelines, and automate processes. Should understand data profiling, data cleansing, and data validation techniques to ensure the accuracy, completeness, and consistency of the data. Knowledge of data privacy and compliance regulations is also important.
• Deep understanding of distributed systems and parallel computing concepts.
• Should be familiar with concepts like data partitioning, parallel processing, fault tolerance, and cluster management.
• Should be familiar with different data storage technologies and NoSQL databases like Apache HBase, Apache Cassandra, MongoDB, or Amazon DynamoDB. Should understand the trade-offs between different storage options and select the appropriate one based on the use case and requirements.
• Should be able to design efficient data schemas that optimize data storage, retrieval, and processing. Should understand concepts such as entity relationship modeling, dimensional modeling, and schema evolution
• Should have experience in real-time data processing techniques. Be familiar with stream processing frameworks like Apache Flink, Apache Kafka Streams, or Apache Storm. Understand concepts like event-driven architectures, message queues, and real-time analytics for building real-time data pipelines.

Education

General Education

• BSc in Computer Science/Engineering or related field.
• Evidence of strong industry/sector participation and relevant professional certifications such as:
  • - Azure Data Engineer Associate
  • - Databricks Certified Data Engineer Associate
  • - Databricks Certified Data Engineer Professional
  • - Amazon Web Services (AWS) Certified Data Analytics – Specialty
  • - Cloudera Data Platform Generalist Certification
  • - Data Science Council of America (DASCA) Associate Big Data Engineer
  • - Data Science Council of America (DASCA) Senior Big Data Engineer
  • - Google Professional Data Engineer
  • - IBM Certified Solution Architect – Cloud Pak for Data v4.x
  • - IBM Certified Solution Architect – Data Warehouse V1

Experience

General Experience

• At least 3 years' developing, deploying, and managing robust ETL/ELT data solutions, preferably in a reputable Financial Institution or FinTech company.