Offer summary

Qualifications:

Bachelor’s degree in Computer Science, Information Technology, or a related field., 5+ years of experience in data engineering with a focus on ETL., Proficient in IBM DataStage and related tools, with strong SQL skills., Experience with cloud services such as AWS, Azure, or Google Cloud Platform. .

Key responsabilities:

Design and implement data pipeline architectures utilizing DataStage.

Develop ETL processes for data extraction, transformation, and loading.

Collaborate with data scientists and analysts to define data requirements and ensure data quality.

Lead and mentor junior data engineers while optimizing performance of data processing workflows.

Job description

Overview

The Senior Data Engineer with expertise in DataStage plays a critical role in our organization by designing, developing, and maintaining robust data pipeline solutions. As an experienced professional, you will ensure that our data management practices align with industry best standards, meeting the organization’s data-driven goals. This role is vital for enabling data analytics, reporting, and business intelligence initiatives, which are essential for our strategic decision-making processes. As a Senior Data Engineer, you will lead projects that enhance our data processing capabilities, ensuring high performance and reliability of our data architecture. You will collaborate cross-functionally with data scientists, analysts, and other engineers to provide reliable data that is tailored to business needs. Your deep understanding of ETL processes, data integration, and data warehousing principles will facilitate seamless data flow across systems, directly contributing to the organization’s operational effectiveness and strategic objectives.

Key Responsibilities

Design and implement data pipeline architectures utilizing DataStage.
Develop ETL processes for data extraction, transformation, and loading.
Collaborate with data scientists and analysts to define data requirements.
Ensure data quality and consistency throughout the data lifecycle.
Optimize performance of data processing and ETL workflows.
Debug and resolve data issues in a timely manner.
Implement data integration strategies with various databases and applications.
Monitor and manage data pipeline performance and reliability.
Maintain documentation of data processes and technical specifications.
Lead and mentor junior data engineers in best practices.
Research and implement new data technologies and methodologies.
Work with cloud-based technologies for data storage and processing.
Develop and enforce data governance policies and procedures.
Conduct regular audits of data processes to ensure compliance.
Participate in Agile development processes and sprint planning.

Required Qualifications

Bachelor’s degree in Computer Science, Information Technology, or a related field.
5+ years of experience in data engineering with a focus on ETL.
Proficient in IBM DataStage and related tools.
Strong experience with SQL and relational databases.
Hands-on experience with big data technologies such as Hadoop or Spark.
Proven ability to design and implement data models.
Experience with cloud services such as AWS, Azure, or Google Cloud Platform.
Familiarity with data warehousing concepts and tools.
Solid understanding of data governance principles and best practices.
Excellent troubleshooting and problem-solving skills.
Strong communication and interpersonal skills.
Ability to work effectively in a team-oriented, collaborative environment.
Experience with Agile software development methodologies.
Knowledge of Python or Java for data processing is a plus.
Data analysis experience is beneficial.
Certifications in Data Engineering or Cloud Technologies are preferred.

SKILL SET

Azure Data Factory, SQL, Databricks, Snowflake, Python, Pyspark, Data warehousing, Java, Perl, DataStage

Required profile