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Experience with modern data platforms (Azure Synapse, Databricks, Redshift, Big Query, Snowflake). Expertise in ETL/ELT, SQL, and cloud data integration tools (Azure Data Factory, AWS Glue, Informatica.
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Comprehensive foundation in SQL, data modeling, data warehousing, and data analysis. Proficiency in Python, PySpark Scala, Java, SQL, Airflow, dbt. Utilize programming languages like Java, Pyspark, Python and Open Source RDBMS and NoSQL databases, and Cloud-based data warehousing services such as Redshift and Snowflake.
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Exp designing and delivering data engineering solutions with Databricks Exp in Azure Databricks Experience in Data Engineer in zure Big Data Environment Expertise in ETL tools i.e. (Infomatica, Talend, SSIS, Data Stage) Expertise in Implementing Data Warehousing Solutions Exp with working in Agile (KANBAN, Scrumban) environment Exp in zure stack ( zure Data Lake, zure Data Factory) Exp in Scala or Python, T-SQL.
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Experience with master data (MDM), metadata, and data governance tools. Skill Advancement: Work with the leadership team to develop a personalized training plan to enhance your data engineering skills.
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Metadata and Data Policy Management: Support and administer the implementation of metadata management and master data policies. In this dynamic role as a Data Engineer, you'll be at the forefront of shaping our data landscape.
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At least 2 years of experience in data engineering. Here, you'll immerse yourself in a world of data management and governance, learning to design models and use advanced tools. Data Solution Implementation: Contribute to the design and execution of prototypes, proofs of concept, and data solutions.
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You won't just be filling a position; you'll be embarking on a journey where your skills in designing data workflows and developing innovative data solutions will be crucial. Demonstrated ability to deliver scalable data solutions using compatible programming languages.
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Technical Integration: Develop and implement technical requirements into our data workflows, collaborating closely with your manager and senior engineers. Ability to oversee data lifecycle management, from ideation to retirement.
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Skilled in modern data platforms (Azure Synapse, Databricks, Redshift, Big Query, Snowflake). Expertise in ETL/ELT, SQL, and cloud data integration tools (Azure Data Factory, AWS Glue, Informatica, etc.
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As you collaborate with experienced mentors and senior engineers, your contributions will be pivotal in building enterprise-class data pipelines. Familiarity with Continuous Integration and Continuous Delivery systems and tools (Azure DevOps, GitHub.
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Our business is guided by our people helping people philosophy which includes our team members. Knowledge of cloud technologies (Azure, AWS, GCP). Collaborative Development: Engage in system analysis, coding, testing, and debugging, in partnership with mentors and senior engineers.
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Applicants should also have a demonstrated understanding and experience using software and tools including big data tools like Kafka, Spark; relational SQL databases including Big Query or equivalent; workflow management and pipeline tools such as Airflow, and object function/object-oriented scripting languages including Scala, C.
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Proven experience in SQL, data modeling, data warehousing, and data analysis. Programming languages: Java, Pyspark, Python and Open Source RDBMS and NoSQL databases and Cloud based data warehousing services such as Redshift and Snowflake.
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Experience in master data (MDM), metadata, and data governance tools (Alation, Erwin, Collibra, Azure Purview). Mentorship and Leadership: Guide and support data engineering teams, enhancing business data processes and systems.
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We offer the flexibility of remote work for residents in these locations, allowing you to contribute from the comfort of your own home. Coding Mentorship: Review and guide the code of junior developers, fostering a culture of learning and growth.
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