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Experience with at least one major Massively Parallel Processing (MPP) or cloud database technology (Snowflake, Databricks, Big Query). Hands-on production experience with data pipeline orchestration systems such as Airflow for creating and maintaining data pipelines.
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4 years of experience in Working with SQL, Databricks, Spark and/or other Big Data technologies. 2 years of experience in Experience working with large-scale data processing and storage using Azure Data Factory, Integration Runtime, Data Lake, Databricks, Spark, Azure ML, Snowflake, SAS Dataflux.
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Advanced experience in SQL in big data warehouse systems such as Snowflake, BigQuery, Databricks, etc. Internal knowledge of open source or related big data technologies. As a member of the Data Engineering Web3 team, you own the ETL/ELT pipelines and data warehouse that are used to analyze trends and activity in our Web3 product offerings.
$195,000 a yearFull-timeExpandUpdated Today - UpvoteDownvoteShare Job
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Working closely across groups, such as the product, engineering, data science, and external partners for data modeling, general management of data life cycle, data governance and processes for meeting regulatory and legal requirements.
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Big Data Technologies: Proficiency in Databricks, Spark, PySpark, Scala, and SQL. Data Engineering Fundamentals: Expertise in ETL/ELT processes, data pipelines, data modeling, schema design, and data warehousing.
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Experience with big data technologies (Spark, Clickhouse, Redshift, Snowflake etc.) Define data engineering standards and best practices and drive operational excellence. Proven success in communication with database users, software engineers and senior management to collect requirements, discuss data modeling decisions and define data engineering strategies.
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Experience with digital data from ad serving platforms (e.g. Google Campaign Manager, Other adservers), campaign planning tools (e.g. Prisma, Lumina, MediaOcean), website analytics software (e.g. Adobe Analytics, Google Analytics), paid search engine marketing data sources (e.g. Adwords, Marin.
$180,000 a yearFull-timeExpandUpdated Today - UpvoteDownvoteShare Job
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Strong experience with distributed data architectures and big data processing technologies (Spark, EMR, Hadoop, Hive) Discerning appreciation of best practices in designing data lakes/lake houses, mentoring junior members, peer review and recommendation.
$171,000 a yearFull-timeExpandUpdated Today - UpvoteDownvoteShare Job
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Softrams is a Maryland and Virginia-based small business information technology, consulting, and solutions provider specializing in emerging technologies for UX/UI, mobile apps, DevOps, big data analytics, data science, and cyber security.
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Position OverviewOur Client is in search of a Data Architect who exhibits deep technical expertise and proficiency in spearheading the design and execution of enduring data initiatives.
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Experience data mining in distributed systems such as Databricks/Google Big Query/Snowflake. Build automated, scalable, repeatable, and integrated analysis using modern big data architectures in data ecosystems such as Databricks, Snowflake, Google Big Query.
$220,660 a yearFull-timeExpandUpdated Today - UpvoteDownvoteShare Job
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Experience must include two (2) years of experience in data mining and development of ETL processes; distributed data architectures and big data processing technologies such as Spark, EMR, Hadoop and Hive; and Realtime Frameworks, collection, and processing Realtime data using kinesis Data Streams, KCL, KDA and Firehoses.
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Experience in database structure work and in building dashboards with Tableau and/or Power BI, Google Data Studio, Datorama, and Domo is required; knowledge of visual techniques for data analysis and presentation is a plus.
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Final interview with our VP Data. In the role of Data Analyst, you will work across Data Analytics, Data Engineering, BI Engineering related tasks, exercising excellent problem solving, data wrangling and analytical storytelling You will be responsible for helping to transform data from our services and existing reports and Tableau dashboards into consumable data Explores and dashboards in our platform.
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Strong Technical Background: Proficiency in programming languages commonly used in data engineering, such as Python, Java, Scala, or SQL. Experience with data processing frameworks and tools like Apache Spark (including Databricks), and Hadoop and knowledge of database technologies like SQL databases (e.g., MySQL, PostgreSQL.
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