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Required Skills: Platform Engineering: Proficiency in Python, Scala, or SQL. Expertise in Apache Spark, Hadoop, or Apache Kafka. ML Ops: Proficient in Python, R, or Java for ML algorithms.
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Experience in at least one modern programming language such as Python, Java, Go, Rust, and proficiency in SQL. Experience in technologies such as Hadoop, Spark, Kafka, Redis, Cassandra, Pandas, Dask, Airflow, Apache Beam, MongoDb, Hive, Impala, Hazelcast, Athena, Presto.
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Data pipelines, Python, Java, Scala, Git, Spark, Hadoop, AWS, Apache Airflow, SQL, React. Big data processing, e.g., Spark/Hadoop. Proficient in Python, Java, or Scala.
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Language - Python, Shell scripts, SQL, pyspark, Java (optional), React or Angular Js. Proficient in Linux CLI commands, shell scripting, SQL, Programming language like (Python or Java.
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Proficiency in data engineering and data visualization tools/languages such as Python, SQL, Data Lake, Tableau. Proficiency with big data technologies (e.g., Hadoop, Spark), database frameworks (e.g., SQL, NoSQL), and cloud services (e.g., AWS, GCP.
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Strong experience in developing ETL pipelines using Microsoft SQL Server Integration Services, Python, and familiarity with big data/cloud databases like Google BigQuery and Snowflake. 4+ years of experience in data validation or complex data intensive analysis that utilizes (big) data manipulation and processing techniques (SQL, MySQL, Hadoop, Spark etc) to ensure (connected) datasets are of high quality and therefore fit for analysis/reporting purposes.
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Must have 6 months of experience in any two of the following next gen tools and technologies: Hadoop, HIVE, Impala, Apache Drill, Pentaho, Paxata, Databricks, Tamr, Datastax, Datameer, Splunk, Sumologic, Mapreduce, Python, Scala, R, Spark, Kafka, Dremio, AWS, Azure Platform, Google Cloud Platform, Cloudera, Hortonworks, Oozie, NoSQL, HBase, Elasticsearch, Cassandra, Flink, Flume, Snowflake, Redshift, EMR, Neo4j.
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5+ years of experience in Database Engineering primarily in AWS Redshift, RDS/Aurora, DynamoDB, DMS, Glue. Proven experience in building data pipelines and database applicationsStrong coding and scripting experience with Python, PowerShell or similar languages.
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3+ years of experience in application development including Python, SQL, Scala, or Java. 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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Work with tools, languages, data processing frameworks, and databases such as R, Python, SQL, MongoDB, Redis, Hadoop, Spark, Hive, Scala, BigTable, Cassandra, Presto, and Strom. Write complex SQL queries to support analytics needs.
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2+ years experience with Distributed data/computing tools (MapReduce, Hadoop, Hive, EMR, Kafka, Spark, or MySQL) 1+ years of experience with a public cloud (AWS, Microsoft Azure, Google Cloud.
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This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). 1+ years of data warehousing experience (Snowflake or DeltaLake.
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Work with a team of developers with deep experience in machine learning, distributed microservices, and full stack systems. New York City (Hybrid On-Site): $138,500 - $158,100 for Data Engineer. As a Capital One Data Engineer, you’ll have the opportunity to be on the forefront of driving a major transformation within Capital One.
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At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors, who solve real problems and meet real customer needs. 2+ years of experience with UNIX/Linux including basic commands and shell scripting.
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Strong programming skills in languages such as Python, SQL, or Java. - Experience with big data processing frameworks and tools such as Apache Spark, Hadoop, or AWS Glue. - Proficiency in working with relational and NoSQL databases, as well as SQL and data modeling.
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