
Lead/Senior Data Engineer
4 weeks ago
About the Role :
We are seeking a talented Lead Data Engineer to join our team and play a pivotal role in transforming raw data into valuable insights. As a Data Engineer, you will design, develop, and maintain robust data pipelines and infrastructure to support our organization's analytics and decision-making processes.
Responsibilities :
- Data Pipeline Development : Build and maintain scalable data pipelines to extract, transform, and load (ETL) data from various sources (e.g., databases, APIs, files) into data warehouses or data lakes.
- Data Infrastructure : Design, implement, and manage data infrastructure components, including data warehouses, data lakes, and data marts.
- Data Quality : Ensure data quality by implementing data validation, cleansing, and standardization processes.
- Team Management : Able to handle team.
- Performance Optimization : Optimize data pipelines and infrastructure for performance and efficiency.
- Collaboration : Collaborate with data analysts, scientists, and business stakeholders to understand their data needs and translate them into technical requirements.
- Tool and Technology Selection : Evaluate and select appropriate data engineering tools and technologies (e.g., SQL, Python, Spark, Hadoop, cloud platforms).
- Documentation : Create and maintain clear and comprehensive documentation for data pipelines, infrastructure, and processes.
Skills :
- Strong proficiency in SQL and at least one programming language (e.g., Python, Java).
- Experience with data warehousing and data lake technologies (e.g., Snowflake, AWS Redshift, Databricks).
- Knowledge of cloud platforms (e.g., AWS, GCP, Azure) and cloud-based data services.
- Understanding of data modeling and data architecture concepts.
- Experience with ETL/ELT tools and frameworks.
- Excellent problem-solving and analytical skills.
- Ability to work independently and as part of a team.
Preferred Qualifications :
- Experience with real-time data processing and streaming technologies (e.g., Kafka, Flink).
- Knowledge of machine learning and artificial intelligence concepts.
- Experience with data visualization tools (e.g., Tableau, Power BI).
- Certification in cloud platforms or data engineering.
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