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Data Engineer
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Role: Data Engineer (Adobe Environment experience)
Locations eligible for this role: India OR Czech Republic
Working time zone: EMEA Hours
Location: 100% remote
Working hours; 8 hours per day (40 hours per week)
Key Responsibilities:
- Design, build, and maintain scalable and robust data pipelines to support data integration and data transformation processes.
- Implement and manage Adobe platform integrations to streamline data workflows. Tech Stack includes but not limited to Redshift, DBT, Starbust, Snowflake, Fivetran, openshift, Adobe on Adobe or Rainfocus.
- Develop complex SQL queries for data analysis and ensure the integrity of data querying processes.
- Employ a variety of data transformation techniques, including hashing, to prepare data for analysis or downstream processing.
- Experience with ETL (Extract, Transform, Load) or ELT (Extract, Load, Transform) processes to efficiently manage data workflows.
- If applicable, work with streaming data, implementing solutions to ingest, process, and manage real-time data feeds.
- Set up QA (Quality Assurance) protocols to ensure the accuracy and quality of data.
- Conduct pressure testing of data pipelines to identify and resolve vulnerabilities or performance bottlenecks.
- Break down complex data issues into digestible and manageable components to streamline problem-solving and communication.
- Collaborate with cross-functional teams, including data scientists, business analysts, and IT staff, to support data-driven decision-making across the organization.
- Stay current with industry trends and developments in data engineering and proactively suggest improvements to data systems and processes.
Qualifications:
- Bachelor's degree in Computer Science, Information Technology, or a related field; Master's degree is a plus.
- Proven experience as a Data Engineer or in a similar role.
- Expertise in Python programming for data manipulation and automation.
- Strong proficiency in SQL and experience with relational databases.
- Familiarity with Adobe tools and platforms, and the ability to integrate them into data processes.
- Understanding of data querying, data transformation, and normalization techniques.
- Experience with ETL or ELT tools and frameworks.
- Knowledge of streaming data platforms is advantageous but not required.
- Strong analytical skills and the ability to work independently.
- Excellent problem-solving abilities and attention to detail.
- Strong communication skills and the ability to work collaboratively in a team environment.