Our client is seeking a talented and experienced Data Engineer to join their team. In this role, you will play a key role in designing, developing, and maintaining our data infrastructure and systems to support data-driven decision-making and business operations

Responsibilities:

• Design, develop, and maintain scalable data pipelines and ETL processes to ingest, process, and transform large volumes of structured and unstructured data from diverse sources.
• Collaborate with cross-functional teams, including data scientists, analysts, and business stakeholders, to understand data requirements and design optimal data solutions.
• Build and optimize data models and schemas to support data analytics, reporting, and machine learning initiatives.
• Develop and implement data quality and validation processes to ensure the accuracy, completeness, and reliability of data.
• Optimize data storage, retrieval, and processing performance to meet performance and scalability requirements.
• Implement data governance and security policies to protect sensitive data and ensure compliance with regulatory requirements.
• Evaluate and recommend new tools, technologies, and frameworks to enhance the capabilities and efficiency of our data infrastructure.
• Troubleshoot and resolve data-related issues and performance bottlenecks in collaboration with technical teams.
• Document data architecture, processes, and best practices to facilitate knowledge sharing and ensure maintainability and scalability.
• Stay current on emerging trends and best practices in data engineering, big data technologies, and cloud computing.

Qualifications:

• Bachelor’s degree in Computer Science, Engineering, or related field; Master’s degree preferred.
• Years of experience in data engineering, database development, or related roles, with a strong focus on building and maintaining data pipelines and ETL processes.
• Proficiency in programming languages such as Python, Java, or Scala, and experience with data processing frameworks such as Apache Spark, Apache Flink, or Apache Beam.
• Experience with distributed computing and big data technologies such as Hadoop, HDFS, Spark, Kafka, and Hive.
• Strong understanding of relational and NoSQL databases, data warehousing concepts, and SQL query optimization.
• Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform, and familiarity with cloud-based data services such as Amazon Redshift, Google BigQuery, or Azure Data Lake.
• Excellent problem-solving and analytical skills, with the ability to troubleshoot complex data issues and performance bottlenecks.
• Strong communication and collaboration skills, with the ability to work effectively in cross-functional teams and communicate technical concepts to non-technical stakeholders.