Overall High-level Skills ETL developer ( Minimum 7 to 8 + years' experience)
The ETL Talend Developer job description is multifaceted & a combination of technical skills, an understanding of business processes, and data analysis capabilities.
Roles/Responsibilities:
Design and Development - Developing ETL Pipelines: ETL Developers code and configure the pipelines that automate data movement and transformation. This involves writing scripts or using ETL tools like Talen DI and Big Data on-prem & Cloud
Data Management and Quality - Ensuring Data Quality: They implement measures to ensure data accuracy and integrity throughout the ETL process. This includes data validation, cleansing, deduplication, and error handling to ensure reliable and usable data.
Designing a Data Warehouse and DWBI Strong concepts
Performance Tuning: They are responsible for optimizing ETL processes for speed and efficiency, addressing bottlenecks, and ensuring the ETL system can handle the volume, velocity, and variety of data.
Collaboration & Support Collaborating with Stakeholders: ETL Developers work closely with business analysts, data scientists, and IT teams to understand data requirements and deliver the data infrastructure that supports business goals.
Continuous Learning - Staying Updated: The field of data management and analytics is rapidly evolving, so ETL Developers must stay updated with the best practices in ETL, data warehousing, and business intelligence.
ETL jobs and env Troubleshooting/ Debugging skills are essential for identifying and fixing issues within ETL processes and data scripts. ETL Developers must be adept at using debugging tools and techniques to maintain high-quality data flows.
RUN ops activities - Support Collaborating with Stakeholders: ETL Developers work closely with business analysts, IT teams
Support Other ETL Developers and Teams
Good understanding of Project management and SDLC process flow
Key Technical Skills
1. ETL Tools: Experience with one or more ETL tools like Talend, ADF, Azure Cloud tools, Databricks, BigData Hadoop Spark on Cloud, and On-PREM experience
2. Code deployment and Migration process and manage the Code repo like GIT, SVN, Nexus
3. Databases: A strong understanding of relational databases (such as MySQL, Teradata, Oracle, and SQL Server) and knowledge of SQL is essential. Experience with NoSQL databases like MongoDB or Cassandra is a plus.
4. DWBI - Data Warehousing Solutions: Familiarity with data warehousing architectures ( and technologies Big Query, Snowflake,
5. Knowledge of scripting languages (Python, Bash, Perl, etc.) Programming language proficiency (JavaScript, Java, C++, etc.) SQL, NoSQL, Hadoop, and other database engineering specialties. Extensive knowledge of warehouse architectural techniques such as MOLAP, ROLAP, and EDW.
6. Big Data Technologies: Knowledge of big data technologies can be beneficial, especially for handling large-scale data processing. Like Spark , Databricks
7. Scripting Language - Knowledge of scripting languages (such as Java, SQLs Python, Perl, or Shell scripting) is beneficial for automating ETL tasks, developing custom transformation logic, and integrating ETL processes with other systems and tools.
8. Repositories: SVN, GIT and Nexus
9. Tools: Maven, Jenkins, Hive, Oozie, Maestro, Toad 8.x, SQL developer and Putty.
10. RDBMS: Oracle 11g/10g/9i/8i/7X, Oracle 10g (RAC, Data Guard & Streams, and (Golden Gate).
11. Operating Systems: HP-UX 10.x, 11.x, AIX 5.1, 5.2, 5.3, Red Hat Linux RHEL
12. Languages: Java SQL, PL/SQL, T-SQL, UNIX Shell Scripting, Bash and Perl Scripting.
Analytical Skills
Data Analysis: Ability to analyze data sources, understand data relationships, and develop strategies to extract, transform, and load data effectively with env and jobs-related issues
Soft Skills
Communication: Strong oral and written communication skills are necessary for collaborating with team members and stakeholders, documenting ETL processes, and explaining technical details clearly.
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