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YOUR SKILLS AND EXPERTISEBachelor’s degree in computer science, data science or a related field with five (5) or more years of working as a data engineer, ETL developer and/or data warehouse DBA.STANDOUT QUALIFICATIONS:Experience with Cloud-based data services and solutions (Azure Synapse / Data Lake, AWS RedShift, Snowflake, GCP Big Query)Experience partnering with Analytics and Data Science teams in building out production grade GenAI/ML solutions.
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Experience with Cloud-based data services and solutions (Azure Synapse / Data Lake, AWS RedShift, Snowflake, GCP Big Query) Bachelor’s degree in computer science, data science or a related field with five (5) or more years of working as a data engineer, ETL developer and/or data warehouse DBA.
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Experience with big data tools and architectures, such as Cloudera Hadoop, HDFS, Hive, and Spark. Experience partnering with Analytics and Data Science teams in building out production grade GenAI/ML solutions.
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Proficient in popular technologies and cloud services, such as Kafka, Redis, Flink, TensorFlow, Triton, AWS services, and containerized environments (Docker, K8s). Solid experience in big data engineering, with working knowledge of Hadoop, Apache Spark, Python, and SQL.
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Experience with BI/Visualization tools Knowledge of version control systems such as Git. Experience utilizing Agile methodology Knowledge of ITIL processes Strong communication, project management and organizational skills Basic understanding of Operating systems, networking concepts and application architecture patterns Ability to code with scripting languages such as Python, Bash, groovy etc., Knowledge of big data toolset: Hadoop, Spark, Kafka, Hive, sqoop etc.
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Experience with data management technologies such as Databricks, Apache Spark, Hadoop, Kafka. Experience with common data science tools such as Python, R, PyTorch, TensorFlow, Keras, NLTK, Spacy, or Neo4j, and a good understanding of modeling platforms such as SageMaker, Databricks, and Dataiku.
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Proven experience with cloud platforms (e.g., AWS, Azure, Google Cloud) and big data technologies (e.g., Hadoop, Spark). Responsible for technical leadership, design, and development of contemporary platform architectures such as Microservices, Cloud Computing, Big Data, Web, Mobile, and AI/ML.
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Experience developing and deploying Machine Learning solutions on cloud platforms (e.g., AWS, Azure, or Google Cloud Platform). 8+ years of experience in developing business applications for Machine Learning and Data Science workloads.
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Implement and utilize leading big data methodologies (AWS, Hadoop/EMR, Spark, Kafka, Snowflake and Talend) with cloud/on premise hybrid hosting solutions, on a multi-team/product level.
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At least 4 years of experience in data engineering working with Big Data Technologies: Apache Spark, Pyspark, Hadoop, and DataBricks with delta lake. At least 1 year of experience working with the following Cloud technologies: AWS, Azure, GitHub, Bamboo, Chef or Terraform.
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Experience with cloud computing platforms (, AWS, Azure, GCP) and cloud native computingProficiency in programming languages like Python, Java, Scala, C#, SQLExpertise in big data technologies such as Hadoop, Spark, Kafka, and NoSQL databasesKnowledge of data modeling, ETL processes, and data warehousing conceptsExceptional problem-solving abilities and teamwork skills.
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THE ROLE:As a key member in the Advanced Data Analytics team, the Data Analyst will work with this and a cross-functional team to develop and execute the data analytics strategy and apply to Oshkosh Corporation products.
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Familiarity with big data technologies such as Apache Spark, Hadoop, and Kafka. Experience with cloud platforms such as AWS, GCP, or Azure for deploying and managing machine learning models.
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5+ years working experience with key open source big-data projects as a contributor or committer including Apache Spark, Apache Flink, Trino, Apache Kafka, Apache Hive, Apache Arrow, Apache Hadoop, Delta Lake, Apache Iceberg.
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Working knowledge of telematics interfaces and streaming solutions (MQTT, NiFi, Kafka, etc. Design and develop scalable Change Data Capture (CDC) and ETL solutions to deliver data from source systems to analytics platforms (structured and unstructured; batch and streaming.
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