Sr. Data Engr - (Datastage /Teradata /Big Data) Job Description Template
As a Sr. Data Engineer, you will be responsible for developing, testing, and maintaining architectures for data processing. You'll play a critical role in leveraging Datastage, Teradata, and Big Data technologies to create efficient data pipelines and support the organization's analytical and decision-making processes.
Responsibilities
- Design and develop reliable data pipelines using Datastage.
- Implement and manage data storage solutions with Teradata.
- Construct scalable big data solutions to handle large volumes of data.
- Optimize and tune data processing systems for performance and reliability.
- Collaborate with data scientists and analysts to understand data requirements.
- Maintain data quality and integrity across different platforms.
- Develop and implement data security policies and practices.
- Monitor, troubleshoot, and resolve data-related issues in a timely manner.
Qualifications
- Bachelor’s degree in Computer Science, Engineering, or related field.
- 7+ years of experience in data engineering or related field.
- Proven experience with Datastage, Teradata, and Big Data technologies.
- Strong understanding of data architecture and ETL processes.
- Excellent problem-solving and analytical skills.
- Experience with data modeling and database design.
- Ability to work independently and as part of a team.
- Effective communication skills, both written and verbal.
Skills
- Datastage
- Teradata
- Big Data technologies (e.g., Hadoop, Spark)
- SQL
- ETL processes
- Data modeling
- Performance tuning
- Data security
Frequently Asked Questions
A Senior Data Engineer with expertise in Datastage, Teradata, and Big Data is responsible for designing, building, and maintaining scalable data processing systems. They work with large datasets, utilizing Datastage for ETL processes, Teradata for data warehousing, and Big Data technologies like Hadoop and Spark to ensure efficient data flow and storage. Their goal is to develop robust data pipelines that support data analysis and business decision-making.
To become a Senior Data Engineer specializing in Datastage, Teradata, and Big Data, one should have a strong background in computer science or related fields, along with substantial experience in data engineering. It's crucial to gain expertise in ETL processes, data warehousing, and Big Data technologies. Hands-on experience with tools like Datastage and databases like Teradata is necessary. Typically, progressing to a senior role requires at least 5-7 years of experience and possibly a master's degree in data-focused disciplines.
The average salary for a Senior Data Engineer specializing in Datastage, Teradata, and Big Data varies by location and company size but generally reflects a competitive level due to the high demand for skilled professionals in this field. These engineers can expect compensation packages that include a base salary, bonuses, and other benefits, reflecting their valuable expertise in managing complex data environments and driving data strategies.
Qualifications for a Senior Data Engineer in this domain typically include a bachelor's or master’s degree in computer science, data engineering, or a related field. In-depth knowledge of ETL tools like Datastage, proficiency in data warehousing with Teradata, and experience with Big Data technologies such as Hadoop and Spark are essential. Strong problem-solving skills and the ability to design efficient data architectures are also critical to this role.
A Senior Data Engineer focusing on Datastage, Teradata, and Big Data must possess advanced skills in ETL design, data modeling, and implementing data warehouse solutions. They are responsible for developing and optimizing data pipelines, ensuring data quality and integrity, and integrating diverse data sources. Proficiency in programming languages like SQL, Python, and Java, along with experience in utilizing Big Data frameworks, is crucial to effectively fulfilling their duties in complex data environments.