Solomon Page
Sr Marketing Advanced Analytics - Data Engineer(Tableau)
Solomon Page, New York, New York, us, 10261
Our client is seeking a highly skilled Data Engineer & Tableau Developer to design, build, and maintain scalable, auditable, and high-quality data solutions. This role supports enterprise analytics by developing robust data pipelines, conducting deep-dive data analysis, ensuring data quality, and delivering clear visual insights through Tableau dashboards. The ideal candidate brings strong expertise in Databricks, Spark, Snowflake, SQL, and Tableau, along with the ability to collaborate closely with analysts, data scientists, and business teams.
Responsibilities
Design, build, and maintain scalable data pipelines using Databricks (Spark/Scala/Python/SQL) and Snowflake.
Manage the full data validation lifecycle, including source-to-target reconciliation, data profiling, and anomaly detection.
Conduct deep-dive data mining to identify trends, inconsistencies, and business opportunities.
Develop and maintain Tableau dashboards and visualizations to drive transparency and decision-making.
Implement automated data quality checks, alerts for pipeline failures, and audit flagging.
Collaborate with analysts, data scientists, and business stakeholders to understand requirements and deliver reliable data products.
Optimize existing pipelines for performance, scalability, and operational efficiency.
Document data lineage, pipeline logic, workflows, and metadata.
Required Qualifications
Hands-on experience building scalable data pipelines using Databricks (Spark/Scala/Python/SQL) and Snowflake.
Strong SQL development skills for extraction, transformation, and performance tuning.
Expertise in source-to-target reconciliation, auditing, and anomaly detection across large datasets.
Proven ability to troubleshoot Spark performance issues.
Solid understanding of Snowflake data loading and update patterns.
Strong experience developing Tableau dashboards with parameters, performance optimization, and data-driven designs.
Strong understanding of the data validation lifecycle.
Ability to clearly document pipelines, workflows, logic, and requirements.
Preferred Skills
Knowledge of advanced data profiling, anomaly detection, and predictive modeling techniques.
Experience collaborating with business stakeholders to translate requirements into reliable data solutions.
Familiarity with documenting data lineage, metadata, and transformation logic.
Strong communication skills with the ability to explain technical findings to non-technical audiences.
Ability to work independently with minimal supervision while managing multiple priorities.
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Responsibilities
Design, build, and maintain scalable data pipelines using Databricks (Spark/Scala/Python/SQL) and Snowflake.
Manage the full data validation lifecycle, including source-to-target reconciliation, data profiling, and anomaly detection.
Conduct deep-dive data mining to identify trends, inconsistencies, and business opportunities.
Develop and maintain Tableau dashboards and visualizations to drive transparency and decision-making.
Implement automated data quality checks, alerts for pipeline failures, and audit flagging.
Collaborate with analysts, data scientists, and business stakeholders to understand requirements and deliver reliable data products.
Optimize existing pipelines for performance, scalability, and operational efficiency.
Document data lineage, pipeline logic, workflows, and metadata.
Required Qualifications
Hands-on experience building scalable data pipelines using Databricks (Spark/Scala/Python/SQL) and Snowflake.
Strong SQL development skills for extraction, transformation, and performance tuning.
Expertise in source-to-target reconciliation, auditing, and anomaly detection across large datasets.
Proven ability to troubleshoot Spark performance issues.
Solid understanding of Snowflake data loading and update patterns.
Strong experience developing Tableau dashboards with parameters, performance optimization, and data-driven designs.
Strong understanding of the data validation lifecycle.
Ability to clearly document pipelines, workflows, logic, and requirements.
Preferred Skills
Knowledge of advanced data profiling, anomaly detection, and predictive modeling techniques.
Experience collaborating with business stakeholders to translate requirements into reliable data solutions.
Familiarity with documenting data lineage, metadata, and transformation logic.
Strong communication skills with the ability to explain technical findings to non-technical audiences.
Ability to work independently with minimal supervision while managing multiple priorities.
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