ANALYTICS ENGINEERING

We are seeking a skilled Analytics Engineer to join our team.
In this role, you will be responsible for developing and maintaining data pipelines, optimizing data infrastructure, and enabling data-driven decision-making through insightful analysis and reporting.
The ideal candidate will have a strong background in data engineering, analytics, and a keen ability to translate business requirements into technical solutions.
Key Responsibilities.
Data Pipeline Development.
Design, build, and maintain scalable data pipelines to ensure the efficient extraction, transformation, and loading (ETL) of data from various sources.
Data Infrastructure.
Develop and optimize data infrastructure to support analytics and reporting needs.
Implement and manage data warehousing solutions.
Data Integration.
Integrate data from diverse sources, including databases, APIs, and third-party tools, to create a unified and accessible data environment.
Data Analysis.
Perform advanced data analysis to identify trends, patterns, and insights that support business objectives.
Create and maintain dashboards, reports, and visualizations.
Collaboration.
Work closely with data scientists, analysts, and business stakeholders to understand data requirements and deliver actionable insights.
Data Quality.
Monitor data quality and integrity.
Implement data validation and cleansing processes to ensure accurate and reliable data.
Documentation.
Document data processes, pipeline architectures, and system configurations.
Ensure that documentation is up-to-date and accessible.
Innovation.
Stay current with industry trends and emerging technologies.
Recommend and implement new tools and methodologies to enhance data capabilities.
Qualifications.
Education.
Bachelor's degree in Computer Science, Data Science, Statistics, Engineering, or a related field (or equivalent experience).
Experience.
+- years of experience in data engineering, analytics, or a related role.
Skills.
Proficiency in SQL and experience with relational databases (, PostgreSQL, MySQL).
Experience with data pipeline tools and frameworks (, Apache Airflow, Talend).
Familiarity with data warehousing solutions (, Snowflake, Redshift, BigQuery).
Knowledge of programming languages such as Python, R, or Scala.
Strong analytical skills and experience with data visualization tools (, Tableau, Power BI).
Understanding of ETL processes and data modeling concepts.
Excellent problem-solving skills and attention to detail.
Preferred Qualifications.
Experience with cloud-based data platforms (, AWS, Google Cloud, Azure).
Knowledge of big data technologies (, Hadoop, Spark).
Experience in a specific industry relevant to the company's focus (, finance, healthcare).
Advanced degree in a relevant field.