Data Engineer must have skills
(Pyspark Azure ADF Databricks ETL SQL)
The Data Engineer plays a crucial role in the organization by building and maintaining the infrastructure necessary for data generation transformation and storage. This role is important as it supports the creation of reliable scalable data pipelines that facilitate data analysis and reporting for the business. As a Data Engineer you will work closely with data scientists analysts and the IT team to ensure that data flows seamlessly across different systems. You will also contribute to the organization s data governance efforts to ensure accessibility and security of data assets. By leveraging your knowledge of data architecture and engineering practices you will help optimize data processing and storage solutions. Ultimately your work will enable teams to extract actionable insights from data which is critical for informed decisionmaking.
Key Responsibilities:
- Design develop and maintain robust data pipelines to facilitate data collection and processing.
- Ensure effective data management and storage through appropriate architecture solutions.
- Collaborate with analysts to understand data requirements and implement solutions that meet their needs.
- Perform ETL (Extract Transform Load) processes to integrate data from various sources.
- Implement data modeling techniques that support analytics and reporting efforts.
- Utilize big data technologies to work with large datasets effectively.
- Monitor and optimize data pipeline performance and troubleshoot issues as they arise.
- Manage databases and create automated reporting and dashboards.
- Work with cloud services (AWS Azure GCP) for data storage and processing solutions.
- Enforce best practices in data governance to ensure data quality and security.
- Document data processes architecture and workflows for clarity and compliance.
- Participate in data architecture discussions and propose improvements to existing systems.
- Provide support for data access ensuring users can retrieve the data they need without complications.
- Stay updated on industry trends and emerging technologies related to data engineering.
- Assist in training and mentoring junior team members on data engineering practices.
Required Qualifications:
- Bachelor s or Master s degree in Computer Science Engineering or related field.
- Proven experience as a Data Engineer or in a related role in data architecture or data warehousing.
- Strong knowledge of SQL and experience working with relational databases.
- Experience with big data technologies such as Hadoop Spark or Kafka.
- Proficiency in programming languages such as Python Java or Scala.
- Handson experience in ETL tools and data pipeline development.
- Familiarity with cloud platforms (e.g. AWS Azure Google Cloud).
- Understanding of data modeling concepts and best practices.
- Knowledge of data governance frameworks and compliance standards.
- Experience with version control systems (e.g. Git).
- Strong analytical and problemsolving skills.
- Ability to work collaboratively in a team environment.
- Excellent written and verbal communication skills.
- Understanding of machine learning concepts is a plus.
- Continuous learner with a passion for new technologies and data.
- Experience with visualization tools like Tableau or Power BI is preferred.
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