Data Engineer

Job Description Roles & Responsibilities The data engineer is responsible for designing, developing, and maintaining the infrastructure and systems required for data storage, processing, and analysis for AI initiatives. They play a crucial role in building and managing the data pipelines that enable efficient and reliable data integration, transformation, and delivery for all Al projects. Key Responsibilities: Designs and develops data pipelines that extract data from various sources, transform it into the desired format, and load it into the appropriate data storage systems Collaborates with AI developers, data scientists and analysts to optimize models and algorithms for data quality, security, and governance Integrates data from different sources, including databases, data warehouses, APIs, and external systems Ensures data consistency and integrity during the integration process, performing data validation and cleaning as needed Transforms raw data into a usable format by applying data cleansing, aggregation, filtering, and enrichment techniques Optimizes data pipelines and data processing workflows for performance, scalability, and efficiency Monitors and tunes data systems, identifies and resolves performance bottlenecks, and implements caching and indexing strategies to enhance query performance Implements data quality checks and validations within data pipelines to ensure the accuracy, consistency, and completeness of data Supports the governance of data and algorithms used for analysis, analytical applications, and automated decision making Desired Candidate Profile A bachelor's degree in computer science, data science, software engineering, information systems, or related quantitative field; master's degree preferred At least six years of work experience in data management disciplines, including data integration, modeling, optimization and data quality, or other areas directly relevant to data engineering responsibilities and tasks Proven project experience developing and maintaining data pipelines for AI projects Technical Skills: Expert knowledge in Apache technologies such as Kafka, Airflow, and Spark to build scalable and efficient data pipelines Ability to design, build, and deploy data solutions that capture, explore, transform, and utilize data to support AI, ML, and Bl Strong ability in programming languages such as Java, Python, and C/C++ Ability in data science languages/tools such as SQL, R, SAS, or Excel Proficiency in the design and implementation of modern data architectures and concepts such as cloud services (AWS, Azure, GCP) and modern data warehouse tools (Snowflake, Databricks) Experience with database technologies such as SQL, NoSQL, Oracle, Hadoop, or Teradata Ability to collaborate within and across teams of different technical knowledge to support delivery and educate end users on data products Expert problem-solving skills, including debugging skills, allowing the determination of sources of issues in unfamiliar code or systems, and the ability to recognize and solve repetitive problems Key Competencies: Excellent business acumen and interpersonal skills; able to work across business lines at a senior level to influence and effect change to achieve common goals. Ability to describe business use cases/outcomes, data sources and management concepts, and analytical approaches/options Ability to translate among the languages used by executive, business, IT, and quant stakeholders. Company Industry InternetE-commerceDotcom Department / Functional Area IT Software Keywords Data Engineer Get real-time job updates only on our App