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Micro-batch streaming and continuous streaming process in Databricks for high latency, low latency and ultra-low latency of data accordingly by using inbuilt Apache spark modules. Strong hands-on expertise in building Data engineering solutions using Java, Apache Spark and Scala.
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As a Staff Engineer for our Data Platform team, you will be responsible for modernizing our data platform and practice. 7+ years of professional experience as a Data Engineer, focusing on building scalable data solutions.
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As a Capital One Lead Data Engineer, you’ll have the opportunity to be on the forefront of driving a major transformation within Capital One. Utilize programming languages like Java, Scala, Python and Open Source RDBMS and NoSQL databases and Cloud based data warehousing services such as Redshift and Snowflake.
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Experience in one of the public cloud providers – GCP, Azure, AWS.Experience with relational SQL and NoSQL databases, including Postgres and MongoDB.Experience with workflow management tools: Airflow, AWS data pipeline, Google Cloud Composer, etc.
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AWS Data Engineer. Strong hands on exposure to AWS Analytics services particulary Lambda,Step functions,EMR, Athena, Glue, Data-Pipelines. Developer will be developing data ingestion pipelines from heterogenous sources like databases, Files, APIs, Kafka streaming etc using a variety of services.
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5 years of experience must include: Data analytics and statistical analysis of financial risk data; Policy and regulatory analysis; Data analytics tools including: R, Excel, and PL/SQL; Anti-Money Laundering (AML) and Know Your Client (KYC) guidelines; Oracle and relational databases; and User Acceptance Testing (UAT) and defect management.
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Synechron is looking for a Cloud Data engineer with a background in Python, Pyspark, SQL and data warehousing for enterprise level systems. Experience in any cloud data warehouse like Synapse, Big Query, Redshift, Snowflake.
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Experience in data architecture, data governance, data modeling, data transformation (from converting data, to data cleansing, to building data structures) data lineage, data Integration, and master data management.
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Proven experience working with Snowflake, DBT, Fivetran, AWS Glue, Python, SageMaker, DB2, SQLServer, and Informatica technologies in a data engineering or analytics role with 8-10 years of experience.
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As a Capital One Senior Manager Data Engineer, you’ll have the opportunity to be on the forefront of driving a major transformation within Capital One. 3+ years of data warehousing experience (Redshift or Snowflake.
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Expertise in multiple technologies across software engineering (e.g. Java, Python, Golang), data architecture/engineering (e.g. Spark/Databricks, Snowflake, BigQuery/Redshift/Synapse) Cloud-native data platforms, services, OSS options for at least some of: data ingestion (from messages buses, databases, APIs), processing (batch, streaming), orchestration, storage, serving, cataloging, quality monitoring.
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3 year of experience in Banking industry specifically in Financial Crimes Data Governance for Sanction Screening, Anti Money Laundering and KYC. Will closely work with Chief Data Office (CDO) and Financial Crimes Data Officer teams to handle the data analysis requests, internal controls, performance tuning, impact analysis requests.
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Experience with modern data engineering tools such as Talend, DBT, Databricks, Snowflake and data visualization tools such as PowerBI, Tableau, ThoughtSpot. Deep understanding and proven experience in Databricks, Azure Data Factory, Synapse.
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Define data mapping and lineage to produce accurate reconciliations across multiple sources. The candidate will also be responsible for data mapping and lineage definition in order to produce accurate reconciliations across multiple sources.
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Building the reports/dashboard for data management and clinical team for data review. Providing EDC technical expertise to Data Management and to the clinical study team members to support study decisions.
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Title: data engineer Company: Mercury Data Science in Jersey City, NJ
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