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Data Engineer

Addo Ai

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1+ year Experience of designing, building and operationalizing large-scale enterprise data solutions and applications using one or more of cloud data and analytics services in combination with 3rd parties.
Hands-on experience with 1 or more of data Ingestion technologies like Azure Data Factory, GCP DataFlow, GCP Fusion, apache AirFlow, AWS Kinesis, AWS Glue, Apache Nifi, and Spark.
Experience of designing and building production data pipelines from ingestion to consumption within a hybrid big data architecture, using Java, Python, Scala, etc.
Proven experience writing complex SQL queries, stored procedures, etc.
Hands-on experience with 1 or more data transformation technologies like Spark, Hive, Azure Dataflow, Azure DataBricks, GCP data proc, GCP dataflow, AWS EMR, and AWS Glue.
Experience with NoSQL data stores like HBase, Cassandra, etc.
Hands-on experience with 1 or more of data storage and EDW technologies like AWS Redshift, GCP BigQuery, Azure Synapse, Azure Data Lake, AWS S3, google cloud storage, HDFS, Parquet, and ORC.
Hands-on experience with 1 or more reporting technologies like AWS quick sight GCP data studio, Looker, PowerBI, Tableau, and Apache superset.
Experience introducing and operationalizing self-service data preparation tools e.g. Alteryx, Data Prep, Trifacta, Paxata.

Responsibilities:

Designing and implementing data transformation, ingestion, and curation functions on the cloud using cloud-native or custom programming.
Designing and building production-grade data pipelines from ingestion to consumption within a hybrid big data architecture, using Java, Scala or Python
Performing detailed assessments of current state data platforms and creating an appropriate transition path to GCP/Azure/AWS.
Optimizing data pipelines for performance and cost for large-scale data lakes.