Applied Intelligence, the people who love using data to tell a story. We’re also the world’s largest team of data scientists, data engineers, and experts in machine learning and AI. A great day for us? Solving big problems using the latest tech, serious brain power, and deep knowledge of just about every industry. We believe a mix of data, analytics, automation, and responsible AI can do almost anything—spark digital metamorphoses, widen the range of what humans can do, and breathe life into smart products and services. Want to join our crew of sharp analytical minds? Visit us here to find out more about Applied Intelligence.
A Spark Big Data engineering pro—someone who thrives in a team setting where you can use your creative and analytical prowess to obliterate problems. You’re passionate about digital technology, and you take pride in making a tangible difference. You have communication and people skills in spades, along with strong leadership chops. Complex issues don’t faze you thanks to your razor-sharp critical thinking skills. Working in an information systems environment makes you more than happy.
- Consult as part of a team that’s in charge of building end-to-end digital transformation capabilities, and lead fast-moving development teams using Agile methodologies.
- Design and build Big Data and real-time analytics solutions using industry standard technologies, and work with data architects to make sure Big Data solutions align with technology direction.
- Lead by example, role-modeling best practices for unit testing, CI/CD, performance testing, capacity planning, documentation, monitoring, alerting, and incident response.
- Keep everyone from individual contributors to top executives in the loop about progress, communicating across organizations and levels. If critical issues block progress, refer them up the chain of command to be resolved in a timely manner.Optimize NLU model by implementing NLP systems, performing intent classification and entity extraction, and user testing Develop and maintain digital conversational flows, dialog Research, Architect, Prototype, and Test Dialogue Management system and Natural Language Generator Connect to data source (e. g. multiple xml documents) and query database
- Pinpoint and clarify key issues that need action, lead the response, and articulate results clearly in actionable form.
Here’s What You Need:
- A Bachelor’s degree in Computer Science, Engineering, or Technical Science, or 12 years’ experience programming and building large-scale data or analytics solutions operating in production environments
- Minimum of 2 years’ experience designing and implementing large-scale data pipelines for data curation, feature engineering, and machine learning, using Spark in combination with pySpark, Java, Scala, or Python
- Minimum of 1 year’s experience designing and building performant data tiers, or refactoring existing ones, that supports scaled AI and Analytics, using different Cloud-native data stores on AWS, Azure, and Google (such as Redshift, S3, Big Query, or SQLDW), as well as using NoSQL and Graph Stores
- Minimum of 1 year’s experience designing and building streaming data ingestion, analysis, and processing pipelines using Kafka, Kafka Streams, Spark Streaming, and similar cloud-native technologies
- Minimum of 1 year’s experience in performance engineering, profiling and debugging very large Big Data and machine learning production solutions on Spark and Cloud-native technologies
Bonus Points if:
- You have experience designing and building secured and governed Big Data ETL pipelines, using Talend or Informatica technologies for data curation and analysis of large production deployed solutions
- You have experience designing and implementing large-scale data warehousing and analytics solutions working with RDBMS (such as Oracle, Teradata, DB2, Netezza, SAS), and grasping the challenges and limitations of these traditional solutions
- You’ve got experience working with Databricks, SageMaker, and other Cloud-native tools
- You’re familiar with implementing smart data preparation tools such as Palate, Trifacta, or Tamr for enhancing analytics solutions
- You have experience building Business Data Catalogs or Data Marketplaces for powering business analytics using technologies such as Alation, Collibra, Informatica, or custom solutions
Applicants for employment in the US must have work authorization that does not now or in the future require sponsorship of a visa for employment authorization in the United States and with Accenture.
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