AVP Head of Division Audit leading audit initiatives for Capital Access Platforms division. Overseeing audit projects, managing a team, and enhancing risk management processes.
About the role
- Assistant Vice President managing and designing data pipelines and applications for enterprise at EXLService. Responsible for leveraging big data and cloud solutions for optimal performance and innovation.
Responsibilities
- Responsible for working independently and with a team to architect, design, implement and manage data pipelines and data-driven applications on Modern Data platforms on both on-premises and Cloud platforms (Azure PaaS, AWS EKS).
- Design, implement and deliver large scale enterprise applications using big data open-source solutions such as Apache Hadoop, Apache Spark, Kafka, and Elasticsearch.
- Implement data pipelines and data-driven applications using C#, Python on distributed computing frameworks like EKS, Presto, AWS Glue, Apache Spark etc.
- Partner with cross-functional platform teams to build Python and C# based Reconciliation tools, to streamline Fund reporting and help Asset Managers.
- Create and maintain optimal data pipeline architecture.
- Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and Big Data technologies.
- Execute and Automate Extract, Transform & Load (ETL) operations on large datasets using Big Data tools like Spark, Sqoop, MapReduce.
- Design and develop data structures that support high performing and scalable analytic applications on one or more of these databases Hive, Impala, NoSQL Databases – HBase, Apache Cassandra, Vertica, or MongoDB.
- Lead the enhancement of existing infrastructure and internalize the latest innovation in technologies like Pyspark, SQL, C# and Scala.
- Leverage automation, cognitive and science-based techniques to manage data, predict scenarios and prescribe actions.
- Design and build data services that deal with big data (>90PB) at low latency for a variety of use-cases spanning near-real-time analytics and machine intelligence using both Stream and Batch processing frameworks on Hadoop ecosystem technologies (e.g. Yarn, HDFS, Presto, Spark, Flink, Beam).
- Work closely with Data Science teams to integrate data, algorithms into data lake systems and automate different Machine Learning workflows and assist with data infrastructure needs.
- Harness the power of data, machine learning and modern tech to build cutting edge exception predictions, income anomalies detection techniques and algorithms to enhance and scaling the Fund Reporting.
- Design and implement reporting and visualization for unstructured and structured data sets using visualization tools such as Tableau, Zoom data, Qlik, etc.
- Review existing computer systems to determine compatibility with projected or identified needs, researches and selects appropriate frameworks, including ensuring forward compatibility of existing systems.
Requirements
- Requires Bachelor’s degree, or foreign equivalent, in Technology, Civil Engineering, or a directly related field plus five (5) years of related professional experience.
- Must have five (5) years of experience in the following: Coding in C#, Python, and SQL with experience in working with large data sets and distributed computing (MapReduce, Hadoop, Hive, Pig, Apache Spark, etc);
- Web Services, XML, and SOAP;
- Hands-on programming experience;
- Gathering and documenting requirements, analysis, and specifications;
- Writing client server software and web solutions in an enterprise environment;
- Hadoop (Cloudera distribution), Impala, HBase, Kafka, Apache Spark, and Spark Streaming;
- Interpreting business requirements and effectively implementing into a software solution;
- Taking direction and mentoring from other senior developers and leadership;
- Translating business requirements into logical and physical file structure design;
- Building and testing rapidly Spark/Map Reduce code in a rapid, iterative manner;
- Data integration on traditional and Hadoop environments;
- Designing and implementing reporting and visualization for unstructured and structured data sets;
- Understanding of the benefits of data warehousing, data architecture, data quality processes, data warehousing design and implementation, table structure, fact, and dimension tables, logical and physical database design, data modeling, reporting process metadata, and ETL processes;
- Using Hadoop scripting to process petabytes of data;
- Unix/Linux shell scripting or similar programming/scripting knowledge.
- Must have three (3) years of experience in the following: - Application architectural design.
Benefits
- Telecommuting Permitted.
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