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8+ Experience programming using data analysis, data modeling, programming, and visualization tools such as Python, SQL, Power BI, Alteryx, and Tableau. 10+ Experience programming using data analysis, data modeling, programming, and visualization tools such as Python, SQL, Power BI, Alteryx, and Tableau.
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Experience with scripting languages (e.g., Python, Bash) and infrastructure as code tools (e.g., Terraform, Ansible) is a plus. Ability to manage and diagnose Data & ETL – Dagster, Airflow, other ETL technologies.
ExpandApply NowActive JobUpdated 22 days ago - UpvoteDownvoteShare Job
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Utilize programming languages like Java, Python, SQL, Node, Go, and Scala, Open Source RDBMS and NoSQL databases, Container Orchestration services including Docker and Kubernetes, Application Architecture like microservices, API, and realtime streaming, ETL and Data Engineering technologies like PySpark, Glue, Snowflake, and a variety of AWS tools and services.
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AWS Glue, Lambda, Athena, Pyspark, Redshift, EMR, AWS RDB, AWS DynamoDB, AWS Glacier, Python. Should have a deep understanding of AWS Services (Redshift, Glue, Lambda, Athena, S3, EC2), Visual Studio, SQL Server, SSIS, Matillion; Python.
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Experience with data integration tools (e.g., Informatica, Talend, Alteryx, SSIS etc) to carry out an ETL (Extract, Transform & Load) to move data from disparate systems to Master Data Management Hub.
$116,200 - $213,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Experience with Master Data Management platforms and tools such as Informatica MDM, C360, Reltio, Profisee, Semarchy. The Data Governance and Data Quality Analyst will specialize in serving EY clients in the areas of Data Strategy, Data Governance, Data Quality, Data Definition and Usage, and Data Management.
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Strong Programming skills e.g. R, Python, SAS, SQL or other languages. Experience with data analytics and visualisation tools (e.g., Alteryx, Tableau, MicroStrategy) Python and PySpark serve as our primary programming languages, in addition to SQL for extracting data from Hadoop and other databases.
$125,000 - $210,000 a yearFull-timeExpandApply NowActive JobUpdated 12 days ago - UpvoteDownvoteShare Job
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Hands on working experience in AWS GLUE ETL tool and having good knowledge on any of the ETL tools(Informatica cloud,Talend etc. Expertise with Python Language and Apache Spark. Strong AWS development experience for data ETL/pipeline/integration/automation work.
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Demonstrating thorough knowledge about ETL tools and techniques, such as tools like Alteryx, Power Query, Azure Data Factory, and Power Apps suite of tools; Demonstrating a thorough level of knowledge in data analytics tools and programming languages, such as Python, R, and SQL.
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3+ years of hands on development experience in AWS Glue, Lambda functions, AWS Athena, Redshift, Pyspark. Strong hands on exposure to AWS Analytics services particulary Lambda,Step functions,EMR, Athena, Glue, Data-Pipelines.
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6 years of experience must include: Apache Spark, Hive, Kafka; Scala, Python; Abinitio, Oracle; Cloud technologies: ORAAS, IBM S3 (Simple Storage Service); Intellij, Eclipse, SQL Developer, Arcadia, Tectia, Tableau, Hue, Jenkins, Sonar; OpenShift, Unravel, Cloudera Manager; and Red Hat Enterprise Linux 8, Tibco.
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Requirements: Requires at least a Bachelor’s degree, or foreign equivalent, in Computer Applications or related field and 6 years of progressive, post-baccalaureate experience as a Reports Analyst, Data Engineer, Module Leader, or related position involving Data Extraction (ETL), Data analysis and reporting in financial domain.
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Proficiency in designing and implementing ETL processes and data integration workflows using tools like Apache Airflow, Informatica, or Talend. Strong proficiency in programming languages such as Python, Java, or Scala, with expertise in data processing frameworks and libraries (e.g., Spark, Hadoop, SQL, etc.
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The ideal candidate will possess extensive knowledge and hands-on experience in Terraform, Docker/Kubernetes, microservices architecture, and data migration, specifically from Oracle to PostgreSQL using ETL tools.
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A Data Engineer also interfaces with other technology teams to extract, transform, and load [ETL] data from a wide variety of data sources. Effectual Data Engineers develop, code, and deploy scripts written in the Python programming language, as Python is the language of Data. All Data Engineers are first and foremost Software Engineers with an understanding of the SDLC process.
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