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As a Director of Data Engineering, you will be instrumental in driving innovation, ensuring data quality, and fostering collaboration across teams to harness the power of data for informed decision-making.
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Drive the adoption of agile methodologies and DevOps practices to ensure efficient and high-quality data engineering processes. Gather, transform, clean, and secure data from many sophisticated, state-of-the-art sources and destination ensuring data quality, integrity and compliance with industry standards.
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Ensure data governance principles adopted, data quality checks and data lineage implemented in each hop of the data. Strongly prefer experience building Data Lake & Data warehouse solutions using ETL,ELT pipelines on Databricks, Snowflake, Azure Data Lake etc.
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Partner with a whole range of teams within the Data organization (Analytics, Data Science, Data Engineering, Data Architecture, Data Quality & Governance, Program Management) to deliver high impact, efficient Data solutions.
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Your role as a Data Engineer: In this role you will be responsible for designing, developing, and maintaining data pipelines in support of data management functions such as data engineering, data integration and data quality and governance activities.
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The candidate will work with the Port Authority of New York and New Jersey (PANYNJ) and will complete general data validation and clean up in support of the PANYNJ Port Department’s development of its asset management program.
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On the Data Science team, we're looking for someone who is comfortable working on a variety of ad auction and placement optimization problems, using experimentation to improve our ads systems, and helping to lead our team in balancing monetization and quality of experience considerations across our streaming service.
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Experience with reliability engineering specifically in areas such as data quality, data observability and incident management. Experience with big data technologies like Trino, Spark, Hadoop, Airflow, Kafka.
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We are hiring for a Principal Product Manager (Technical) to drive the evolution of products which provide Amazon business teams and selling partners (marketplace sellers and retail vendors) with comprehensive, accurate, and standardized metrics in a timely manner to enable high quality, high velocity decisions.
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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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Experience in developing Data Warehouse/Data Marts using, as examples, OBIEE, OBI APPS, Cognos, Business Objects, SPSS, SSIS, SSRS, Informatica Power Center, OWB and ODI. · Experience on design and development of Data Warehouse Architecture for Enterprise Data Warehouse (EDW), Operational data Store (ODS), Operational Data Marts and Data Marts.
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Python, SQL, and spark expertise, along with core competencies required to ship high quality data pipelines and data tools fast. Implement data quality tests and alerting for key donation, donor, and donor engagement variables.
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A minimum of six years' experience in providing complex consultative services in the following focus areas: information strategy, big data architecture, information/data governance, master data management, data quality, data integration particularly in a life science or healthcare setting.
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Own the data accuracy, quality and governance across NDWA (advocacy organizing data) and CiA's (electoral data) programs. Proven knowledge of data governance, accuracy, quality, and security best practices.
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Experienced in several of the following domains: biomedical informatics, outcomes and health services research, clinical trials, clinical decision support, population health and claims analytics, quality metrics and reporting, data security, privacy and regulatory compliance, and data governance.
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data quality jobs Title: data Company: Deloitte in Secaucus, NJ
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