Job
Description
Who We Are Escalent is an award-winning data analytics and advisory firm that helps clients understand human and market behaviors to navigate disruption. As catalysts of progress for more than 40 years, our strategies guide the worldâs leading brands. We accelerate growth by creating a seamless flow between primary, secondary, syndicated, and internal business data, providing consulting and advisory services from insights through implementation. Based on a profound understanding of what drives human beings and markets, we identify actions that build brands, enhance customer experiences, inspire product innovation and boost business productivity. We listen, learn, question, discover, innovate, and deliverâfor each other and our clientsâto make the world work better for people. Why Escalent? Once you join our team you will have the opportunity to... Access experts across industries for maximum learning opportunities including Weekly Knowledge Sharing Sessions, LinkedIn Learning, and more. Gain exposure to a rich variety of research techniques from knowledgeable professionals. Enjoy a remote first/hybrid work environment with a flexible schedule. Obtain insights into the needs and challenges of your clientsâto learn how the worldâs leading brands use research. Experience peace of mind working for a company with a commitment to conducting research ethically. Build lasting relationships with fun colleagues in a culture that values each person. Role Overview: We are looking for a Data Engineer to design, build, and optimize scalable data pipelines and infrastructure that power analytics, machine learning, and business intelligence. You will work closely with data scientists, analysts, and software engineers to ensure efficient data ingestion, transformation, and management. Roles & Responsibilities: Design, develop, and maintain scalable ETL/ELT pipelines to extract, transform, and load data from diverse sources Build and optimize data storage solutions using SQL and NoSQL databases, data lakes, and cloud warehouses (Snowflake, BigQuery, Redshift) Ensure data quality, integrity, and security through automated validation, governance, and monitoring frameworks Collaborate with data scientists and analysts to provide clean, structured, and accessible data for reporting and AI/ML models Implement best practices for performance tuning, indexing, and query optimization to handle large-scale datasets Stay updated with emerging data engineering technologies, architectures, and industry best practices Write clean and structured code as defined in the teamâs coding standards and creating documentation for best practices Stay updated with emerging technologies, frameworks, and industry trends Required Skills: Strong proficiency in Python, SQL, and data processing frameworks (Pandas, Spark, Hadoop) Experience with cloud-based data platforms (AWS, Azure, GCP) and services like S3, Glue, Athena, Data Factory, or BigQuery Solid understanding of database design, data modeling and warehouse architectures Hands-on experience with ETL/ELT pipelines and workflow orchestration tools (Apache Airflow, Prefect, Luigi) Knowledge of APIs, RESTful services and integrating multiple data sources Strong problem-solving and debugging skills in handling large-scale data processing challenges Experience with version control systems (Git, GitHub, GitLab) Ability to work in a team setting Organizational and time management skills Desirable skills: Experience working with Agile development methodologies Experience in building self-service data platforms for business users and analysts Effective skills in written and verbal communication Show more Show less
