About the Role:
At DataSpecta, we develop innovative solutions that shape the business world by unlocking the power of data. We are looking for a passionate
Data Engineer
to join our growing data team, who will transform raw data into meaningful and reliable data products. In this role, you will play a key part in modernizing traditional ETL processes and architecting next-generation data platforms using big data technologies like Spark and Flink.
Responsibilities:
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Design, develop, and manage end-to-end, efficient, and scalable data pipelines using big data processing technologies like Spark and Flink, as well as industry-standard ETL tools
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Create flexible data models and data warehousing solutions to support analytics and reporting processes that meet business needs
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Analyze existing ETL/ELT processes and SQL queries to implement improvements, optimize resource consumption, and enhance performance
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Collaborate closely with data scientists, analysts, and business units to understand data requirements and deliver high-quality data products
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Ensure the implementation of data governance and security standards, including data quality, data lineage, and reliability
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Stay current with new technologies and approaches in the data field and proactively recommend improvements to the existing infrastructure
Required Qualifications:
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Bachelor's degree in Computer Science, Management Information Systems (MIS), Mathematics, or a related field
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3+ years of hands-on experience in Data Engineering or Data Warehousing
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Proven experience in developing large-scale data pipelines and ETL/ELT workflows using Python and Spark
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Hands-on experience with workflow scheduling platforms such as Airflow, Dagster, or similar technologies
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Advanced proficiency in SQL and experience with procedural SQL languages such as Oracle PL/SQL
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Experience working with structured and semi-structured data formats like Parquet, Avro, and JSON
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In-depth knowledge of modern data architectures such as data lakes, data lakehouses, and core data modeling principles
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Experience with at least one industry-standard ETL tool such as ODI, Informatica, or Talend
Preferred Qualifications (Nice to have):
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Experience with data processing and optimization in cloud environments (AWS, Azure, GCP), with a preference for GCP
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Experience with real-time data processing and streaming technologies, such as Kafka
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Familiarity with workflow management platforms like Airflow
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Knowledge of containerization technologies like Docker and Kubernetes, and CI/CD processes
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Familiarity with BI tools such as Power BI
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Experience in the banking or finance industry is a significant advantage
Personal Attributes:
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Excellent communication skills in English, both written and verbal
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Strong analytical thinking, problem-solving skills, and a results-oriented mindset
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A team player with the ability to communicate effectively with stakeholders at all technical levels
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Detail-oriented with a commitment to delivering high-quality work
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