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Experience in Data science, machine learning, or optimization models Experience in Python, Spark, Scala, or R, using open source frameworks (for example: scikit learn, TensorFlow, Pytorch) You are knowledgeable of databases, data warehouse design, cloud storage, and ETL best practices.
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3+ years of experience with data applications and tools (Snowflake, Databricks, Spark, EMR, Presto, Datadog, DBT, etc.) To build this topology graph, ROCI consumes data from a number of BSS/OSS, construction, provisioning, planning, and monitoring platforms to create linkages previously unseen across the company.
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Extensive experience working with various data technologies and tools such as Airflow, Snowflake, Meltano, Fivetran, DBT, AWS, and Looker. By establishing HackerOne's one source of truth and developing data products and solutions on this foundation, we help our Hackers, Customers, and Hackeronies gain insights and make better decisions, thereby empowering the world to build a safer internet.
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Uses coding skills to enable multiple sources to move data through Snowflake, MDM, RDS, and other cloud data environments using tools such as Spark, Striim, Kafka, Snowpipe, Azure Data factory, AWS Glue, Matillion, FiveTran and more.
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Create, maintain and monitor data flows in Spark, Hive, SQL and Presto for consistency, accuracy and lag time. Presto - fast parallel data warehouse and data federation layer. Create different consumers for data in Kafka using Spark Streaming for near time aggregation.
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Familiarity with one of the Data Governance & Data Catalog tools. Cloud: AWS or Azure or GCP in Data Engineering and Analytics streams. Familiarity in Data Engineering tools, data ops tools in On-prem and Cloud eco system.
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Be very familiar with databases & data warehouses: Snowflake, Redshift, BigQuery, Postgres, MySQL, etc. Create beautiful dashboards and reports, and work with customers to create self-service exploration data cubes using Looker.
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Strong Experience with cloud-based data warehouses - e.g., Snowflake, Big Query, Synapse, RedShift, etc. Identify data needs for business and product teams, understand their specific requirements for metrics and analysis, and build efficient and scalable data pipelines to enable data-driven decisions across DICKs.
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Experience with Data management and Data governance processes and standards; Support the governance of LTK's data lakehouse. Profound knowledge of AWS Data services (eg: Redshift, S3, EMR, Glue, RDS, Kinesis, etc.
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Maintain best practices around security and governance Model data management solutions. Proficiency in data engineering tools such as Databricks, Apache Spark, Delta Lake, MLflow, and SQL.
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Data Governance & Security: Collaborate with security teams to establish data governance policies and practices, ensuring compliance with regulations and best practices in data security and privacy.
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Experience with linux/unix/bash scripting is preferred; extensive knowledge of tools useful in manipulating and converting data; facility with numbers and meticulous attention to detail; experience with statistics and statistical programming (R preferred); programming experience with one or more general-purpose programming languages preferred; capacity for learning new technical skills independently; experience with neuroimaging tools (SPM, AFNI, FSL) preferred.
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Utilizing Python, Kotlin, Snowflake, DBT, and Kubernetes, you will play a crucial role in enhancing our data infrastructure. Extensive experience with DBT and Snowflake for data warehousing, including complex SQL/ETL/ELT workflows.
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Be the company's expert on data administration and master data management. Have good working knowledge of AWS data infra systems and Terraform. Bring a system-oriented and software engineering mindset to the Data Engineering practice.
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Our service offerings include anti-money laundering compliance and investigations; Bribery and corruption investigations; forensic accounting; fraud and other financial crime investigations; governance; risk and regulatory advice; regulatory investigations and litigation support and transactional data analytics.
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Title: data governance in Philadelphia, Anoka, Minnesota
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