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Exposure to big data platforms - Snowflake, Redshift, Azure, Matillion, Hadoop. You have a strong background in data quality management and are experienced with SaaS and/or digital sales metrics.
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Expertise in Java, Python, R, and proficiency in big data technologies such as Spark, Databricks, etc. Implement and optimize data processing workflows using Spark, Databricks, and other big data frameworks.
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Would be preferred to have executed end to end implementation/migration of a Data Warehouse and Big Data (Hadoop) project from on prem to GCP (using Google BigQuery, DataFlow, DataProc etc.
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Experience deploying and maintaining pipelines (AWS, Docker, Airflow) and in engineering big-data solutions using technologies like Databricks, S3, and Spark. Feature Engineering and Optimization: Develop and maintain ETL pipelines using orchestration tools such as Airflow and Jenkins; deploy scalable streaming and batch data pipelines to support petabyte scale datasets.
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Big Data Technologies : Experience with big data technologies and tools such as Apache Spark, Hadoop, Apache Cassandra, and distributed computing frameworks for handling large-scale datasets.
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Exposure to big data technologies such as Spark, AI, Data Science, Data Engineering, Hadoop, Cassandra, etc. Minimum 10 years in a technical role delivering projects in Data Analytics, Machine Learning, Cloud Computing Platforms, and Service-oriented architecture, with a preference for Large Language Model (LLM) technology.
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Job Schedulers – Airflow, Oozie or other ETL Scheduler Data Analytics – AWS Cloud Native Services Big data architecture – Python, Scala, Hadoop Bigdata, Hive, Pyspark etc. Data bases (SQL, NoSQL) and Data Platforms (Databricks, Snowflake) Strong skills with Database management, Data modeling and design DevOps and Security CI/CD, Serverless compute, OAuth, SSO, MFA etc.
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The Sr. Enterprise AI Strategy Advisor ( Sr. Project Engineer - Computer Engineering - Data Science/Big Data Mining and Artificial Intelligence ) will execute Space Systems Architect Division mission by leveraging the Aerospace program office and engineering technology group backplane to collaboratively develop and assist in execution of SSC's Enterprise AI Strategy and Implementation plans aligned to both the DoD and AI Strategy documents.
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What You Need to be Successful - (Sr. Project Engineer - Computer Engineering - Data Science/Big Data Mining and Artificial Intelligence) Masters or PhD degree in Systems Engineering, Artificial Intelligence, Data Science, Statistics or Machine Learning.
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Experience with at least one major Massively Parallel Processing (MPP) or cloud database technology (Snowflake, Redshift, Big Query) Expanding, scaling, and standardizing the core foundational principles through consistent observability, lineage, data quality, logging, and alerting across all engineering teams in the Data organization is imperative to the creation of a single pane of glass.
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Architect, design, and code shared libraries in Scala and Python that abstract complex business logic to allow consistent functionality across the Data organization. Maintain detailed documentation of your work and changes to support data quality and data governance requirements.
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Familiarity with data engineering concepts and tools such as data pipelines, ETL processes, SQL, and big data technologies (e.g., Apache Spark, Hadoop). We are seeking a skilled Sr. Martech Software Engineer with expertise in marketing technology platforms (CRM or CDP) such as Adobe Experience Platform (AEP) or similar (e.g. Salesforce, Dynamics, etc), coupled with strong skills in building custom solutions on AWS, proficiency in API development using languages like Python or Java, and some experience in data engineering.
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Stay abreast of emerging technologies and trends in martech, API development, cloud computing, and data engineering to drive innovation and improve martech capabilities. Utilize Python and other relevant programming languages to build robust APIs, microservices, and integrations for seamless data exchange and automation.
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Apply data engineering principles to design and optimize data pipelines for ingesting, processing, and analyzing marketing data. Implement data governance, quality checks, and monitoring to ensure the integrity and reliability of marketing data.
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Configure and integrate platform components to enable seamless data collection, segmentation, personalization, and campaign orchestration. That's why we provide an array of options, expert guidance and always-on tools, that are personalized to meet the needs of your reality – to help support you physically, financially and emotionally through the big milestones and in your everyday life.
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big data jobs Company: Saxon Global
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