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Data Warehousing Guru: Familiarity with data warehousing solutions like ClickHouse, Redshift, BigQuery, or Snowflake for efficient data storage and retrieval. Data Engineering & Backend Proficiency: 7+ years of experience as a Big Data Engineer or Backend Engineer, demonstrating a strong understanding of data systems design and development.
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We're searching for a talented Data Engineer to join our growing team and play a key role in building the foundation for our data-driven future. Cloud Native: Hands-on experience utilizing cloud platforms (AWS, Azure, GCP) for data processing, storage, and orchestration, optimizing for performance and cost.
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Extensiveknowledge of data warehousing concepts andhands-on experience deploying pipelines using Databricks. In addition, you will play a key role, often as an engagement lead, on client engagements related to data warehousing, ETL development, data integrations, and data modeling.
$125,000 - $160,000 a yearFull-timeExpandApply NowActive JobUpdated 1 month ago - UpvoteDownvoteShare Job
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Programming languages: Java, Pyspark, Python and Open Source RDBMS and NoSQL databases and Cloud based data warehousing services such as Redshift and Snowflake. In this dynamic role as a Senior Data Engineer, youll be at the forefront of shaping and implementing cutting-edge data solutions.
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Two years of collective experience in the application of data engineering, data analytics, data warehousing, business intelligence, database administration and data integration concepts and methodologies.
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ODS offers state of the art publishing solutions through our customer-centric applications and services include electronic document delivery, web applications, high-speed digital printing (color and black & white), automated composition, offset printing, warehousing and fulfillment services.
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Collaborates with the Data Architect & Engineer in the creation and maintenance of Data Standards, Best Practices, Data Modeling, Management & Governance (including Data Quality & Metadata) and Data Security (including PII.
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Stream Processing Master: Experience with batch and stream processing technologies like Apache Kafka and Spark to handle data pipelines of all sizes. Data Quality Champion: Experience implementing robust data quality assurance techniques and best practices to ensure data accuracy and reliability.
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Experience working with large-scale datasets and data warehousing technologies (, iSeries IBM). Proven experience (2 years) as a Data Analyst, Data Engineer, or similar role, with a focus on data cleansing and preparation.
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Data Storytelling: Ability to communicate complex data concepts and insights clearly to both technical and non-technical stakeholders. Design, build, and maintain robust data pipelines for both batch and stream processing, ensuring efficient data movement throughout the system.
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Implement and maintain high data quality standards with robust data quality assurance practices. Develop and manage our ClickHouse-based data warehouse, optimizing data storage and retrieval for large datasets.
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Utilize cloud technologies effectively for data pipeline orchestration, processing, and storage, optimizing for both performance and cost-efficiency. Data Wrangling Wizard: Expertise in Python and SQL for efficient data manipulation and analysis.
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Profound hands-on experience with Snowflake's data warehousing solutions, Databricks' analytics platform, and the orchestration capabilities of Airflow. Engineer sophisticated data pipelines using dbt, Airflow, and Snowflake, with special emphasis on performance optimization and data integrity using Great Expectations.
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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. 4+ years of data warehousing experience (Redshift or Snowflake.
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7+ years of experience in data engineering, with a focus on data integration, data transformation, and data warehousing. Data Engineer (AWS Cloud) NOTE : This is a full-time employment opportunity.
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