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Get to know the Role:
As the Data Engineer in the Data Technology team, you will be working on all aspects of Data, from Platform and Infra build out to pipeline engineering and writing tooling/services for augmenting and fronting the core platform. You will be responsible for building and maintaining the state-of-the-art data Life Cycle management platform, including acquisition, storage, processing and consumption channels. The team works closely with Data scientists, Product Managers, Finance, Legal, Compliance and business stakeholders across the SEA in understanding and tailoring the offerings to their needs. As a member of the Data Tech team, you will be an early adopter and contributor to various open source big data technologies and you are encouraged to think out of the box and have fun exploring the latest patterns and designs in the fields of Software and Data Engineering.
The day-to-day activities: Build and manage the data asset using some of the most scalable and resilient open source big data technologies like Airflow, Spark, Snowflake, Kafka, Kubernetes, ElasticSearch, Superset and more on cloud infrastructure.
The must haves:
Job ID: 116665735
Skills:
Metadata Management, Databricks, Python, Data lineage techniques, Master data management, Data modeling methodologies, Big Data storage architecture
Skills:
Hadoop, Pyspark, Kafka, Presto, Spark, Python, AI tools, Pinot, pgvector, Codex, vector databases, Claude, Pinecone, Flink, cloud data warehouses, Hudi, Milvus, Weaviate
Skills:
Dependency Injection, Java, BigQuery, Apache Flink, Google Cloud Platform, Linux, PostgreSQL, Kubernetes, Sql
Skills:
Pyspark, Kafka, Terraform, Python, Spark SQL, Apache Spark, Sql, Git, Azure Data Factory, Databricks, Spark Structured Streaming, Airflow, OneLake, Warehouse, Pipelines, CI CD, Microsoft Purview, Dataflows, Event Hubs, Unity Catalog, dbt, Lakehouse, Delta Lake, Microsoft Fabric
Skills:
Java, S3, Scala, Emr, Redshift, Sql, Lambda, Kinesis, Spark, Python, AWS, Step Functions, Lake Formation, Glue, Athena