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Experience in performing ETL and data engineering work by leveraging multiple google cloud components using Dataflow, Data Proc, BigQuery. Google Cloud Platform Services: DataFlow, BigQuery, Cloud Storage, DataProc, Airflow, Composer, Pub/Sub and Memorystore/Redis.
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SQL: 1+ Years (Preferred) Data Warehousing (Snowflake, Databricks, Redshift, BigQuery, Clickhouse, etc). Craft robust ETL and ELT pipelines using tools like dbt, Fivetran, Airbyte, Matillion and/or custom Python.
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Advanced experience in SQL in big data warehouse systems such as Snowflake, BigQuery, Databricks, etc. What you’ll be responsible for:As a member of the Data Engineering - Business ETL team, you own the ETL/ELT pipelines and data warehouse that is used for financial and regulatory reporting.
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Experience with cloud-based data platforms and services (e.g., AWS, Azure, Google Cloud) including familiarity with relevant tools and technologies (e.g., S3, Redshift, BigQuery, etc.) Proficiency in designing and implementing ETL processes and data integration workflows using tools like Apache Airflow, Informatica, or Talend.
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Design, develop and deliver data integration/data extraction solutions using IBM DataStage or other ETL tools and Data Warehouse platforms like Teradata, BigQuery. Tech stack: BigQuery , any ETL tool (Informatica, Talend, DataStage), Dataflow, Dataproc.
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As a member of the Data Engineering Blockchain team, you own the ETL/ELT pipelines and data warehouse that are used to analyze trends and activity on the blockchain. Designing, building and maintaining data ETL/ELT pipelines to source and aggregate the required data for various data analyses and reporting needs, as well as to continually improve the operations, monitoring and performance of the data warehouse.
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As a member of the Data Engineering - Business ETL team, you own the data warehouse and data pipelines that are used for financial and regulatory reporting. Designing, building and maintaining data ETL/ELT pipelines to source and aggregate the required data for various data analyses and reporting needs.
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Our infrastructure – including USDC, a blockchain-based dollar – helps businesses, institutions and developers harness these breakthroughs and capitalize on this major turning point in the evolution of money and technology.
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Expert in one of the domains of ETL/ELT pipelines, feature engineering, data modeling and architecture, or data ingestion. Experience with workflow orchestration management engines such as Airflow, Dagster, DBT, etcExperience with Cloud Services (AWS, Google Cloud, Microsoft Azure, etc.
ExpandApply NowActive JobUpdated 7 days ago - UpvoteDownvoteShare Job
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Build data ingestion processes using Google Cloud ETL tools (Data fusion, Dataflow, Dataproc, Airflow) Usage of Google BigQuery ML and Vertex AI. Usage of business intelligence tools (e.g. Tableau, Looker) and data frameworks (e.g. Hadoop, Google Cloud Platform, SAP.
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CI/CD orchestration (Jenkins, CircleCI, or TravisCI)ETL, data modeling, cloud-based data storage, processingGCP Data Services (Dataflow, BigQuery, Dataproc)Workflow and data pipeline orchestration (Airflow, Oozie, Jenkins, etc)Container orchestration technologies (Kubernetes, OpenStack, Docker swarm, etc)Open source software involvementMonitoring/Logging with technologies like Splunk, ElasticSearch, Logstash/Fluentd, Stackdriver, Time-series databases like InfluxDB etc.
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QUALIFICATIONS:Advanced MS SQL Server knowledge (MS SQL Server 2016+ preferred)Development expertise with MS SQL Server Integration Services (SSIS), dbt and Apache AirflowProficient with cloud DW and ETL/ELT solutions (e.g., Snowflake, BigQuery, Talend, Matillion, etc.
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Experience with workflow orchestration management engines such as Airflow, Dagster, DBT, etc. Experience with Cloud Services (AWS, Google Cloud, Microsoft Azure, etc). Experience in SQL and NoSQL, such as MySQL, PostgreSQL, Cassandra, HBase, Redis, DynamoDB, Neo4j, etc.
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In-depth knowledge and hands-on experience in GCP cloud-native services such as BigQuery, Dataflow, Pub/Sub, Cloud Data Fusion, Cloud Composer and Google Data Studio etc. Experience in architecting and designing solutions leveraging services like Cloud Bigquery, Cloud Data Flow, Cloud Pub OR Sub, Cloud BigTable.
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Speed and efficiency are motivators for our success and our employees live by our company values: Multistakeholder, Mindfulness, Driven by Excellence and High Integrity. Working closely across groups, such as the product, engineering, data science, and external partners for data modeling, general management of data life cycle, data governance and processes for meeting regulatory and legal requirements.
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