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Job Summary:
We are seeking a skilled and experienced Data Engineer to join our team. The ideal candidate will have expertise in Snowflake or Big Data platforms and a strong background in RDBMS skills like Oracle PL/SQL. You will be responsible for designing, developing, and maintaining data pipelines, ensuring data quality, and optimizing database and data platform performance. This role requires a deep understanding of modern data engineering workflows, ETL processes, and database systems.
Key Responsibilities:
Data Engineering:
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Design, develop, and maintain scalable and efficient data pipelines to support business needs.
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Implement ETL/ELT processes to extract, transform, and load data from various sources into Snowflake, Big Data platforms, or RDBMS systems.
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Optimize data workflows for performance, scalability, and reliability.
Snowflake or Big Data Platforms:
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For Snowflake:
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Design and implement data models in Snowflake to support analytical and reporting needs.
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Develop and optimize Snowflake queries, stored procedures, and user-defined functions.
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Manage Snowflake data sharing, security, and access control.
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For Big Data Platforms:
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Work with Big Data technologies such as Hadoop, Spark, Hive, or HDFS to process and analyze large datasets.
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Develop distributed data processing pipelines using Spark (PySpark)
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Optimize Big Data workflows for performance and scalability.
RDBMS Skills (Oracle PL/SQL):
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Write, debug, and optimize complex PL/SQL scripts, stored procedures, functions, and triggers.
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Perform database performance tuning, query optimization, and troubleshooting in Oracle.
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Design and implement database objects such as tables, views, indexes, and constraints.
Data Integration:
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Integrate data from multiple sources, including APIs, flat files, and third-party systems.
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Collaborate with data analysts, data scientists, and business teams to understand data requirements.
Data Quality and Governance:
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Ensure data accuracy, consistency, and integrity across systems.
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Implement data validation and error-handling mechanisms.
Collaboration and Documentation:
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Work closely with cross-functional teams to understand business requirements and translate them into technical solutions.
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Document data pipelines, database designs, and processes for future reference.
Required Skills and Qualifications:
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Technical Expertise:
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Expertise in Snowflake or Big Data platforms:
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Snowflake: Hands-on experience with Snowflake data warehousing, data modeling, and query optimization.
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Big Data Platforms: Experience with Hadoop, Spark (PySpark), Hive, or HDFS for distributed data processing.
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Strong experience in RDBMS skills, particularly Oracle PL/SQL, including stored procedures, functions, triggers, and performance tuning.
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Proficiency in SQL and database design principles.
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Experience with ETL/ELT tools
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Programming Skills:
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Proficiency in scripting languages such as Python and Shell scripting for data processing and automation.
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Data Governance:
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Knowledge of data quality, data governance, and data security best practices.
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Soft Skills:
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Strong problem-solving and analytical skills.
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Excellent communication and collaboration skills.
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Ability to work in a fast-paced, dynamic environment.
Preferred Qualifications:
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Experience with data visualization tools (e.g., Tableau, Power BI).
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Knowledge of CI/CD pipelines for database deployments or Big Data workflows.
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Familiarity with real-time data processing tools (e.g., Kafka, Flink, or Storm).
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Certification in Snowflake, Oracle databases, or Big Data technologies is a plus.
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Knowledge of NO SQL ( either Mongo or Neo4J )
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Job Family Group:
Technology
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Job Family:
Applications Development
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Time Type:
Full time
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Most Relevant Skills
Please see the requirements listed above.
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Other Relevant Skills
For complementary skills, please see above and/or contact the recruiter.
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