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Experience in developing an end-to-end AWS native platform for building Data lakes (S3, Glue (Crawlers, ETL, Catalog), IAM, CodePipeline, CodeCommit, CloudFormation (or Terraform), CloudTrail, CloudWatch, AWS Config, Guard Duty, Secrets Manager, KMS, EC2, Data Visualization Tool: Tableau run on an EC2 or AWS Quicksight), Athena.
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Stay abreast of the latest advancements in Databricks and other relevant technologies to continually enhance data engineering practices. Develop and maintain ETL processes to ingest, transform, and load data from various sources into Databricks Delta Lake.
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Data Processing/Transformations: Vector (VRL), Kafka, Apache Spark, and or general ETL applications & approaches. Keep up-to-date with emerging trends and technologies in data platform engineering, and make recommendations for their adoption as appropriate.
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The Data Operations Manager will also work closely with Engineering, Analytics and Product Management teams, in providing actionable insights and support for strategic initiatives along with building powerful tools for taxonomy administration.
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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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Consulting, Staffing & Staff Augmentation, Managed Services, design thinking, big data, employee engagement, executive hires, digital engineering services, talent development, R&D Labs, Cloud Computing, DataOps, DevOps, RPA, digital transformation, and AIOps.
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This should also include a strong background in data engineering, with expertise in data modeling, ETL processes, and cloud technologies. 5+ years of related experience in data engineering, software engineering, including proven experience as a Data Engineer with expertise in data warehouse technologies.
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Sidekick is an open source ETL framework for syncing data between SaaS tools (Salesforce, Zendesk, Notion, etc) to vector stores, a necessary step in building GPT powered applications. You ideally have a background in data engineering and should be just as comfortable making architectural decisions as implementing them in code.
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What you’ll be responsible for: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.
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Minimum of 5 years using at least one ETL tool such as Microsoft SQL Server Integration Services (SSIS), Microsoft Azure Data Factory, AWS Glue, IBM InfoSphere DataStage, or any ETL applications.
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Experience with data engineering concepts and challenges including data warehouse solutions, ETL, and distributed systems, as well as familiarity with and experience manipulating data in various formats, such as: avro, neo4j, json, cef, csv, w3c, pandas.
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A Master’s degree in Computer Science, Computer Engineering, Electrical Engineering, Operations, Statistics, Data Science or other relevant courses and 3+ years of prior relevant experience.
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Full Time] Data Engineer at Psychic (United States) | BEAMSTART Jobs. Data integration platform for LLMs. You would be the first hire for our company with a founder-like role in engineering, with the possibility for equity-weighted or cash-weighted compensation.
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Nice to have:B.S., M.S., or PhD in a related fieldPublications at conferencesExpertise with either big data infrastructure (e.g. Hadoop/Spark/Flink/Kafka/Airflow/Presto) or with using big data technologies for data processing, ETL, reporting.
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This includes SQL expertise, knowledge of cloud data warehouses, cloud provider services (AWS, Google, Azure), ETL/ELT tools, data modeling/engineering, data science/machine learning, api consumption, scripting (python preferred), general networking knowledge and cloud SaaS applications (Zendesk, Salesforce, Marketo, etc.
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data administrator engineering etl jobs in San Francisco, CA
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