Job Description

Key Responsibilities\
 

• Architect, Design and Implement large-scale data ecosystems including data management, governance and the integration of structured and unstructured data to generate insights leveraging on-premise and cloud-based platforms

• 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 Java, Python on distributed computing frameworks like EMR, Presto, AWS Glue, Athena, Apache Spark, etc
• Partner with cross-functional platform teams to set up KAFKA, Kinesis queues, to streamline message flows and govern the transfer mechanism
• Create and maintain optimal data pipeline architecture. Assemble large, complex data sets that meet functional / non-functional business requirements. Build distributed, scalable, and reliable data pipelines that ingest and process data at scale
• 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
• Drive software design meetings and analyze user needs to determine technical requirements.
• Consult with the end user to prototype, refine, test, and debug programs to meet needs.
• Design and implement solutions that comply with all security policies and procedures, to ensure that the highest level of system and data confidentiality, integrity and availability is maintained.
• Be the leader in enhancing existing infrastructure and internalize the latest innovation in technologies like in-memory (Aerospike, Juno, Graph (Janusgraph, NEO4j), and GPU DB, real-time OLAP, time-series analysis et. al.

• 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 (i.e. sub-second) 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
• Harnessing the power of data, machine learning, and humans and be build cutting edge fraud detection, collusion detection techniques and algorithms to enhance and scaling fraud management platforms.
• Design and implement reporting and visualization for unstructured and structured data sets using visualization tools like Tableau, Zoomdata, 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.

Please be aware that EXL requires all employees to be vaccinated for COVID-19.  This position will require the successful candidate to obtain and show proof of a vaccination.  EXL is an equal opportunity employer, and will provide reasonable accommodation to those individuals who are unable to be vaccinated consistent with federal, state, and local law.

Base Salary Range Disclaimer: The base salary range represents the low and high end of the EXL base salary range for this position. Actual salaries will vary depending on factors including but not limited to: location and experience. The base salary range listed is just one component of EXL's total compensation package for employees. Other rewards may include bonuses, as well as a Paid Time Off policy, and many region specific benefits. 

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