About the Role
We are seeking a talented Senior Data Engineer to join our team and play a pivotal role in transforming raw data into valuable insights. In this role, you will design, develop, and maintain robust data pipelines and infrastructure to support the organization’s analytics and decision-making processes.
Responsibilities
Build and maintain scalable data pipelines to extract, transform, and load (ETL) data from various sources (databases, APIs, files) into data warehouses or data lakes.
Design, implement, and manage data infrastructure components including data warehouses, data lakes, and data marts.
Ensure data quality by implementing data validation, cleansing, and standardization processes.
Optimize data pipelines and infrastructure for performance and efficiency.
Collaborate with data analysts, data scientists, and business stakeholders to understand data needs and translate them into technical requirements.
Evaluate and select appropriate data engineering tools and technologies (SQL, Python, Spark, Hadoop, cloud platforms).
Create and maintain clear and comprehensive documentation for data pipelines, infrastructure, and processes.
Skills
Strong proficiency in SQL and at least one programming language (Python, Java, etc.).
Experience with data warehousing and data lake technologies (Snowflake, AWS Redshift, Databricks, etc.).
Knowledge of cloud platforms (AWS, GCP, Azure) and cloud-based data services.
Strong understanding of data modeling and data architecture concepts.
Hands-on experience with ETL/ELT tools and frameworks.
Excellent problem-solving and analytical skills.
Ability to work both independently and collaboratively in a team environment.
Preferred Qualifications
Experience with real-time data processing and streaming technologies (Kafka, Flink, etc.).
Knowledge of machine learning and artificial intelligence concepts.
Familiarity with data visualization tools (Tableau, Power BI, etc.).
Certification in cloud platforms or data engineering is a plus.