Accountant is responsible for performing monthly, quarterly, and annual accounting activities, including reconciliations, account analysis, and review of financial reports/support for client portfolio companies and subsidiary. The Accountant will ensure compliance with accounting policies and procedures and resolve accounting related issues. RESPONSIBILITIES: Functional Perform monthly/quarterly account analysis and roll-forwards of selected general ledger accounts to ensure accounts properly reflect the company’s financial position in accordance with company policy and GAAP. Review ledger detail, record adjusting journal entries, and prepare supporting schedules for GAAP-based financial statements. Assist in the preparation of property financial statements and work papers monthly. Assist in the preparation of annual audited financial statements, including footnote disclosures, and supporting schedules. Assist in the monthly/quarterly reporting to lenders, joint venture partners and portfolio companies. Coordinate with the treasury team to ensure that all financing transactions are properly and timely accounted for. Prepare monthly cash flow forecasts for portfolio companies and stand-alone investments. Review property-level financial results, mostly prepared by third-parties, to ensure results properly reflect the company’s financial position and are in accordance with GAAP. Prepare bank reconciliations and journal entries as needed. Assess and react to changing business conditions, in terms of their impact to the supported organization. Ensure team’s processes and procedures support the department’s goals according to guidelines and policies. On-board and account for acquisitions, dispositions, and other similar transactions. Relationship Management Accountable to portfolio company’s or joint venture partner’s satisfaction with the accounting team’s performance, responsiveness, and interactions. Become day-to-day go-to person for client Investment Reporting Respond to business partner inquiries and commit to deliverables. Assist other portfolio companies during project initiatives on an as-needed basis. REQUIREMENTS: Mandatory Qualified Chartered Accountants 2023-10-10T07:53:33.84000:00 Mastercard Overview Mastercard is the global technology company behind the world?s fastest payments processing network. We are a vehicle for commerce, a connection to financial systems for the previously excluded, a technology innovation lab, and the home of Priceless�. We ensure every employee can be a part of something bigger and change lives. We believe as our company grows, so should you. We believe in connecting everyone to endless, priceless possibilities. Join a fast-growing team. As a Senior Engineer in the Data Engineering & Analytics team, you will develop data & analytics solutions that sit atop vast datasets gathered by retail stores, restaurants, banks, and other consumer-focused companies. The challenge will be to create high-performance algorithms, cutting-edge analytical techniques and intuitive workflows that allow our users to derive insights from big data that in turn drive their businesses. You will have the opportunity to create high-performance analytic solutions based on data sets measured in the billions of transactions and front-end visualizations to unleash the value of big data. You will have the opportunity to develop data-driven innovative analytical solutions and identify opportunities to support business and client needs in a quantitative manner and facilitate informed recommendations/decisions through activities like building automated data pipelines, designing data architecture/schema, performing jobs in big data cluster by using different execution engines and program languages such as Hive/Impala, Python, Java, Kafka, Spark, R, etc. Your Role Drive the evolution of Data & Services products/platforms with an impact-focused on data engineering. Design and implement scalable data architecture and data pipelines. Solving complex problems with multi-layered data sets, as well as optimizing existing machine learning libraries and frameworks. Provide support for deployed data applications and analytical models by being a trusted advisor to Data Scientists and other data consumers by identifying data problems and guiding issue resolution with partner Data Engineers and source data providers. Ensure proper data governance policies are followed by implementing or validating Data Lineage, Quality checks, classification, etc. Discover, ingest, and incorporate new sources of real-time, streaming, batch, and API-based data into our platform to enhance the insights we get from running tests and expand the ways and properties on which we can test and experiment with new tools to streamline the development, testing, deployment, and running of our data pipelines. Mentor junior colleagues on relevant technical and product trends through training classes Participate in the development of data and analytic infrastructure for product development Continuously innovate and determine new approaches, tools, techniques & technologies to solve business problems and generate business insights & recommendations. Partner with roles across the organization including consultants, engineering, and sales to determine the highest priority problems to solve. Evaluate trade-offs between many analytics solutions to a problem, considering usability, technical feasibility, timelines, and differing stakeholder opinions to make a decision. Break large solutions into smaller, releasable milestones to collect data and feedback from product managers, clients, and other stakeholders. Evangelize releases to users, incorporating feedback, and tracking usage to inform future development. Ensure proper data governance policies are followed by implementing or validating Data Lineage, Quality checks, classification, etc. Work with small, cross-functional teams to define the vision, establish team culture and processes. Consistently focus on key drivers of organization value and prioritize operational activities accordingly. Escalate technical errors or bugs detected in project work Maintain awareness of relevant technical and product trends through self-learning/study, training classes, and job shadowing. Ideal Candidate Qualifications: Working proficiency in using Python/Scala, Spark (tuning jobs), SQL, Hadoop platforms to build Big Data products & platforms. Good programming skills in Java, spring boot and Junit. Experience with performance Tuning of Database Schemas, Databases, SQL, ETL Jobs, and related scripts Knowledge in software development test approaches & frameworks Familiarity with RESTful APIs and micro-services architectures Experience in working with CI/CD. At least 6 years of relevant hands-on experience as a Data Engineer in an individual contributor capacity. Experience in working with Cloud APIs (e.g., Azure, AWS) Experience in working with SQL database like Postgres, Oracle Preferably with hands-on experience with Hadoop big data tools (Hive, Impala, Spark) Experience with data pipeline and workflow management tools: NIFI, Airflow. Comfortable in developing shell scripts for automation. Good troubleshooting and debugging skills. Proficient in standard software development, such as version control, testing, and deployment Demonstrated knowledge of coding and data engineering. Ability to quickly learn and implement new technologies. Ability to Solve complex problems with multi-layered data sets. Ability to innovate and determine new approaches & technologies to solve business problems and generate business insights & recommendations. Ability to multi-task and strong attention to detail Flexibility to work as a member of a matrix based diverse and geographically distributed project teams Good communication skills - both verbal and written ? and strong relationship, collaboration skills, and organizational skills Degree in Computer Architecture, Computer Science, Electrical Engineering or equivalent experience The Following Skills Will Be Considered As a Plus. Experience participating in complex engineering projects in an Agile setting e.g. Scrum Hadoop