Data Engineer/Analyst - Remote

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Job Overview

The Data Engineer/Analyst at SynergisticIT will play a pivotal role in managing and analyzing large datasets to extract valuable insights that drive strategic decision-making. This position encompasses responsibilities such as developing data pipelines, ensuring data quality and integrity, and collaborating with cross-functional teams to translate business needs into technical requirements. The ideal candidate will leverage their engineering and analytical skills to optimize data processing mechanisms and support the data-driven culture within the organization.

Job Responsibilities

• Design, develop, and maintain scalable data pipelines to support data consumption and analysis.
• Collaborate with stakeholders to understand data requirements and translate them into technical specifications.
• Ensure the quality, accuracy, and consistency of data through rigorous testing and validation procedures.
• Monitor data systems for performance and reliability, addressing any issues that may arise.
• Work with large databases, performing data extraction, transformation, and loading (ETL) processes as required.
• Create and maintain documentation for data processes, workflows, and architectural designs.
• Perform data analysis to extract insights and support decision-making processes across the organization.

Qualifications

• Bachelor’s degree in Computer Science, Data Science, Information Technology, or a related field.
• Proven experience in data engineering or data analysis, preferably within a similar industry.
• Strong proficiency in SQL and experience with relational and non-relational databases.
• Familiarity with data processing frameworks such as Apache Spark or Hadoop.
• Knowledge of data visualization tools, such as Tableau, Power BI, or similar software.
• Experience with programming languages such as Python or R.
• Excellent problem-solving skills and the ability to work collaboratively in a remote environment.

Technologies & Tools

The position requires familiarity with a variety of technologies and tools to effectively perform data engineering and analysis tasks. Key technologies include SQL databases (e.g., MySQL, PostgreSQL), NoSQL databases (e.g., MongoDB), data processing frameworks (e.g., Apache Spark), and data visualization platforms (e.g., Tableau, Power BI). Proficiency in programming languages such as Python and R is essential for data manipulation and analysis.

Ideal Candidates

Ideal candidates for this position will possess strong analytical and critical thinking skills, along with a proactive approach to problem-solving. They should demonstrate excellent communication skills, enabling effective collaboration with diverse teams and stakeholders. A genuine passion for data and its applications in driving business decisions, along with a strong desire to grow professionally within a dynamic and evolving work environment, will further distinguish successful applicants in this role.