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High level of proficiency in ETL processes and demonstrated, hands-on experience with technologies such as Databricks, Python, Spark, Scala, JavaScript/JSON, SQL, and Jupyter Notebooks.
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Hands-on experience with big data technologies, including Apache Spark and Databricks Delta Lake. Develop and maintain ETL processes to ingest, transform, and load data from various sources into Databricks Delta Lake.
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Hands-on experience with backend ETL for data extraction & building data model, including scripting and data source integration. Should be hands-on to support development, Triage and Trouble-shoot issues encompassing integration and back-end systems.
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Hands on experience with Snowflake, DBT, Prefect or Airflow. Design and build highly-efficient and scalable ETL pipelines with Snowflake, Airbyte, dbt, and Prefect. Bluesky is a platform that helps organizations optimize costs and maximize returns on their Snowflake investment.
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Hands-on experience & understanding designing, building, and maintaining complex ETL pipelines using Snowflake, Databricks, Kafka, and AWS Glue. You'll be a hands-on leader, actively contributing to the codebase and ensuring the smooth flow of data from various sources to our Snowflake data warehouse.
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As a Data Engineering Principal for a leading digital agency, you will be a hands on, senior data technologist. Hands-on experience of modern software delivery, including CI/CD and DevOps practices with a deep understanding and extensive track record of delivering complex data solutions using Agile methods including Scrum, SAFe etc.
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Practical hands on experience with: NLP (especially operationalization in production models), Advanced machine learning techniques and tools (especially Tensorflow), modern Data Analytics & Visualization tools (Looker preferred.
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Hands-on professional creation of advanced data visualization and dashboards. Hands-on experience with data architecting, data mining, and data modeling. Experience with Data Warehouse and ETL solutions such as SQL Server, Snowflake, Azure, Databricks, Informatica, or similar.
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Hands-on experience with developing and deploying Azure-based solutions by using Azure Data Lake Storage, Azure Databricks, Azure Synapse Analytics, or other Azure services. The ideal candidate for this Senior Data Engineer role will have expertise in Databricks, preferably in building robust ETL solutions, and in Python (PySpark) and Delta tables.
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This role will serve as a hands-on contributor and be a thought leader in the areas of data engineering, cloud data strategy, Business Intelligence, Data Modeling and ETL/ELT. Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
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Your expertise in ETL, Databricks, Python, Spark, Scala, JavaScript/JSON, SQL, and Jupyter Notebooks will be essential in ensuring efficient data processing and analysis. Design, develop, and implement end-to-end data pipelines, utilizing ETL processes and technologies such as Databricks, Python, Spark, Scala, JavaScript/JSON, SQL, and Jupyter Notebooks.
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Hands-on experience with ETL tools, data lakes, and data warehousing solutions (Snowflake, Redshift, BigQuery, etc. Minimum 10 years of experience in data governance, data engineering, and data strategy, with a focus on leadership roles.
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Be credible on technical issues such as data engineering and data science. Monitor and report on adherence to data management standards across the organization and compliance with data-related regulation/regulator mandates, and proactively recommend adjustments or course corrections as appropriate.
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Hands-on experience with DevOps tools such as Jenkins and Terraform for infrastructure automation. Data Engineering: Design, build, and maintain scalable data pipelines and ETL processes using Databricks and other relevant technologies.
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Environment: Fully on-site. Understanding of data modeling/visualization, database design principles, and data governance practices. Perform data cleansing, data integration, and data quality assurance activities to maintain the accuracy and integrity of large datasets.
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