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Report to the Engineering Manager of Banking - Data Engineering. Stay up to date with emerging technologies, best practices, and industry trends in data engineering and software development.
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Hand-on knowledge of ETL and data warehouse technologies (i.e. dbt, Databricks, BigQuery, Redshift, Airflow, Snowflake) As part of our data team, you'll work with stakeholders across the business, including finance, marketing, engineering, product, operations, and support.
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Net, C#, Qlik, Power BI, Machine Learning, Azure Data Factory, RedShift, UiPath, Cloud, RPA, AWS, Redshift, Kinesis, QuickSight, SageMaker, S3, Databricks, AWS Lake Formation, Snowflake, Python, Qlik, Athena, Data Pipeline, Glue, Star Schema, Data Modeling, Performance Tuning, SQL Individual salaries that are offered to a candidate are determined after consideration of numerous factors including but not limited to the candidate’s qualifications, experience, skills, and geography.
$100,000 - $155,000Full-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Experience working with cloud or on-prem Big Data/MPP analytics platform (i.e. SnowFlake,Netezza, Teradata, AWS Redshift, Google BigQuery, Azure Data Warehouse, or similar). Sia Partners is looking for a talented Data Engineer to support our activities within the Data Science Business Unit. You will be working alongside with our Data Science consultants and our clients on Data Engineering topics, including creating relevant data models, developing powerful data pipelines, exposing them through various mechanisms including APIs, and using data visualization tools to efficiently present data.
$94,500 - $122,000 a yearFull-timeExpandApply NowActive JobUpdated 3 days ago - UpvoteDownvoteShare Job
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Experience with big data and workflow management technologies like Hadoop, Spark, Redshift, Athena, Airflow, etc. The Data Platform team is responsible for ingestion of tens of thousands of events per second, data Lakehousing (Databricks), OLTP stores (Hbase, OpenSearch) and APIs. The customers of the Data Platform are the internal business units who use it for data engineering, AI/ML, and Business Intelligence.
$145,000 - $190,000 a yearExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Develop, deploy and maintain data processing pipelines using cloud technology such as AWS, Databricks, Kubernetes, Airflow, Redshift, EMR. 4+ years experience in engineering data pipelines using big data technologies (Python, pySpark, Real-time data platform like Active MQ or Kafka or Kinesis) on large scale data sets.
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And big data platforms like BigQuery, Redshift and Snowflake, etc. (Bonus) Have a good understanding / interest in data engineering and transformation workflows. and big data platforms like BigQuery, Redshift and Snowflake, etc.
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Collaborate with product, data engineering and broader engineering teams to refine data additions to the data warehouse, lead scoring, and dynamic lead routing incentive systems.
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Strong experience identifying complex business insights directly via SQL (Databricks, Redshift, etc.) Familiarity with customer data augmentation, segmentation, custom audiences, and consumer marketing datasets.
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Proficient in Data Warehouse technologies (e.g. Snowflake, AWS Redshift, etc) and in AWS data pipelines (Lambda, AWS glue, Step functions, Airflow etc) You will lead the data engineering team in designing and implementing a cutting-edge data platform and pipelines along with direct collaboration with crucial teams such as Product, Research, and Engineering enhance the data platform and with Security, Legal, and Compliance to help establish and maintain data governance.
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About The Role & TeamWe are seeking a Sr. Data Engineer to join our Data Engineering team within our Enterprise Data Insights organization to build data solutions, design and implement ETL/ELT processes and manage our data platform to enable our cross functional stakeholders.
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Our people extend into all industries we conduct work with our clients in the areas of; data science, data engineering, data strategy, intelligent process automation, data ecosystems, intelligent industry/IoT, enterprise management, customer-first marketing, and data partnerships/disruptors (such as SAP, Microsoft, Google, AWS, Snowflake, Oracle, Adobe, etc.
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Exposure to big data platforms – Snowflake, Redshift, Azure, Matillion, Alteryx, etc. Partner with cross functional teams such as data science, data engineering, product analysts, experimentation and instrumentation teams to contribute to advanced models (MMM, MTA), data pipelines and instrumentation, and build testing roadmap.
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Have 7-10 years of experience working with data warehouse/data lake and ETL architectures, cloud data warehouses (Redshift, Snowflake, RDS) , and experience in Python and SQL, preferably at companies with fast-growing and evolving data needs.
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Prior experience administering relational databases such as Postgresql, Mysql, Oracle and/or Data Warehouses like Redshift, Vertica, etc. You will own and manage our Postgres RDS and Redshift data infrastructure and will be responsible for the successful delivery and availability of data throughout the company.
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data engineering redshift jobs in San Francisco, CA
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