Lead Data Engineer - Vice President

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Job Overview

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:

• Design, develop, and maintain scalable and efficient data pipelines to support business needs.
• Implement ETL/ELT processes to extract, transform, and load data from various sources into Snowflake, Big Data platforms, or RDBMS systems.
• Optimize data workflows for performance, scalability, and reliability.

Snowflake or Big Data Platforms:

• For Snowflake:
  • Design and implement data models in Snowflake to support analytical and reporting needs.
  • Develop and optimize Snowflake queries, stored procedures, and user-defined functions.
  • Manage Snowflake data sharing, security, and access control.
• For Big Data Platforms:
  • Work with Big Data technologies such as Hadoop, Spark, Hive, or HDFS to process and analyze large datasets.
  • Develop distributed data processing pipelines using Spark (PySpark)
  • Optimize Big Data workflows for performance and scalability.

RDBMS Skills (Oracle PL/SQL):

• Write, debug, and optimize complex PL/SQL scripts, stored procedures, functions, and triggers.
• Perform database performance tuning, query optimization, and troubleshooting in Oracle.
• Design and implement database objects such as tables, views, indexes, and constraints.

Data Integration:

• Integrate data from multiple sources, including APIs, flat files, and third-party systems.
• Collaborate with data analysts, data scientists, and business teams to understand data requirements.

Data Quality and Governance:

• Ensure data accuracy, consistency, and integrity across systems.
• Implement data validation and error-handling mechanisms.

Collaboration and Documentation:

• Work closely with cross-functional teams to understand business requirements and translate them into technical solutions.
• Document data pipelines, database designs, and processes for future reference.

Required Skills and Qualifications:

• Technical Expertise:
  • Expertise in Snowflake or Big Data platforms:
    • Snowflake: Hands-on experience with Snowflake data warehousing, data modeling, and query optimization.
    • Big Data Platforms: Experience with Hadoop, Spark (PySpark), Hive, or HDFS for distributed data processing.
  • Strong experience in RDBMS skills, particularly Oracle PL/SQL, including stored procedures, functions, triggers, and performance tuning.
  • Proficiency in SQL and database design principles.
  • Experience with ETL/ELT tools
• Programming Skills:
  • Proficiency in scripting languages such as Python and Shell scripting for data processing and automation.
• Data Governance:
  • Knowledge of data quality, data governance, and data security best practices.
• Soft Skills:
  • Strong problem-solving and analytical skills.
  • Excellent communication and collaboration skills.
  • Ability to work in a fast-paced, dynamic environment.

Preferred Qualifications:

• Experience with data visualization tools (e.g., Tableau, Power BI).
• Knowledge of CI/CD pipelines for database deployments or Big Data workflows.
• Familiarity with real-time data processing tools (e.g., Kafka, Flink, or Storm).
• Certification in Snowflake, Oracle databases, or Big Data technologies is a plus.
• Knowledge of NO SQL ( either Mongo or Neo4J )