Big Data Engineer (R00094397_Houston)
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
A 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 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, DevOps, 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.
Pinpoint and clarify key issues that need action, lead the response and articulate results clearly in actionable form.
Show a strong aptitude for carrying out solutions and translating objectives into a scalable solution that meets end customers’ needs within deadlines.
Collaborate with research teams working on a variety of deep learning and NLP problems.
Design, build and test data Ingestion frameworks for enabling data supply chain pipelines ensuring data governance and data onboarding best practices
Here's what you need:
Bachelor's degree in Computer Science, Engineering, Technical Science or 3 years' of experience in programming and building large scale data/analytics solutions operating in production environments.
Minimum 2+ years' of expertise in designing, implementing large scale data pipelines for data curation, feature engineering and machine learning, using Spark in combination with PySpark, Java, Scala or Python; either on premise or on Cloud (AWS, or Azure). Experience in working with Databricks, SageMaker, Azure Machine Learning and other Cloud native tools is highly desired.
Minimum 1 year of designing and building performant data tiers (or refactoring existing ones), that supports scaled AI and Analytics, using different Cloud native data stores on AWS and Azure (Snowflake, Redshift, S3, Azure Synapse etc.) as well as using NoSQL and Graph Stores.
Minimum 1 year of designing and building streaming data ingestion, analysis and processing pipelines using Kafka, Kafka Streams, Spark Streaming and similar cloud native technologies (Azure Event Hubs, Streamsets, etc)
Bonus points if:
Minimum 1 year of designing and building secured and governed Big Data ETL pipelines, using Talend or IICS / Informatica technologies; for data curation and analysis of large production deployed solutions.
Experience implementing smart data preparation tools such as Paxata and Trifacta for enhancing analytics solutions.
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