Data Architectural Expert
7 days ago
We are seeking a skilled Senior Data Engineer to lead the design and development of data systems that support Markovate's business growth. With 4-6 years of experience in data engineering, you will have advanced knowledge of data architecture, pipeline creation, and big data technologies.
This role demands a proactive individual skilled in designing, building, and maintaining scalable data pipelines, collaborating with cross-functional teams, and ensuring the highest standards of data quality and performance.
Note: Excellent Python programming skills are required for this position.
Key Responsibilities:
- Data Pipeline Development: Design, develop, and maintain scalable data pipelines for data ingestion, processing, and storage.
- Data Architecture Design: Build and optimize data architectures and data models for efficient data storage and retrieval.
- ETL Process Development: Develop complex ETL processes to transform and load data from various sources into data warehouses and data lakes.
- Data Integrity and Quality: Ensure data integrity, quality, and security across all data systems.
- Collaboration and Communication: Collaborate with data scientists, analysts, and other stakeholders to understand data requirements and deliver solutions that meet business needs.
- Monitoring and Optimization: Monitor, troubleshoot, and optimize data pipelines and workflows to ensure high availability and performance.
Candidate Requirements:
- Bachelor's degree in Computer Science, Engineering, or a related field.
- 4-6 years of experience in data engineering and data architecture.
- Proficiency in SQL and at least one programming language (e.g., Python, Java, Scala).
- Advanced experience with cloud data platforms (e.g., AWS, Azure, GCP) and their data services.
- Strong knowledge of ETL tools and frameworks (e.g., Apache NiFi, Talend, Informatica).
- Expertise in data modeling, data structures, and database design.
- Strong analytical and problem-solving skills, with the ability to handle complex data challenges.
- Excellent communication and collaboration skills, with the ability to work independently and as part of a team.
- Experience with data warehousing solutions (e.g., Redshift, BigQuery, Snowflake).
- Hands-on experience with big data technologies (e.g., Hadoop, Spark, Kafka).
- Knowledge of data governance and best practices in data management.
- Familiarity with containerization and orchestration tools (e.g., Docker, Kubernetes).
- Experience with data visualization tools (e.g., Tableau, Power BI).
Estimated Salary: $140,000 - $160,000 per year, based on industry standards and location.
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