Senior Data Engineer

This is a fully remote position, open to applicants in United States.

📋 Description

• Design, construct, implement, and sustain data processing pipelines for ETL from diverse data sources.

• Lead the creation of intricate SQL queries to fulfill analytics requirements.

• Develop technical tools and programs utilizing artificial intelligence, machine learning, and big-data techniques to clean, organize, and transform data.

• Continuously maintain, protect, and update data structures and integrity through automation.

• Assess and suggest tools and technologies for data infrastructure and processing.

• Collaborate with engineers, data scientists, data analysts, product teams, and stakeholders to convert business needs into technical specifications and coded data pipelines.

• Design and scale a contemporary data platform that supports both real-time and batch processing for financial forecasting, risk analytics, and customer insights.

• Uphold standards for data governance, quality, lineage, and compliance.

• Partner with engineering, finance, sales, and compliance stakeholders to develop reliable data models and workflows.

• Assess emerging technologies and lead proofs of concept to shape the data stack.

• Advocate for security, automation, and continuous delivery within data workflows.

• Work with R, Python, SQL, Databricks, Spark, Delta, APIs, data lakes, relational database management systems, and data warehouses.

⛳️ Requirements

• Bachelor's or master's degree in computer science, engineering, or a related discipline.

• 6-8 years of experience in data engineering, particularly with a strong emphasis on financial systems within SaaS platforms.

• Extensive knowledge of Python, SQL, and distributed processing frameworks such as Apache Spark, Databricks, Snowflake, Redshift, and BigQuery.

• Proven experience with cloud-based data platforms, ideally AWS or Azure.

• Practical experience with data orchestration tools like Airflow or dbt.

• Familiarity with data warehouses such as Databricks, Snowflake, Redshift, or BigQuery.

• Strong comprehension of data security, privacy, and compliance issues in the context of financial services.

• Experience handling structured and semi-structured data types like Delta, JSON, Parquet, and Avro at scale.

• Knowledge of modeling datasets in Salesforce, Netsuite, and Anaplan is required.

• Capability to evaluate unusual situations and apply advanced analytical and problem-solving skills.

• Ability to work independently, exercising independent judgment.

• Skill in enhancing relationships and networks with senior internal partners, often necessitating persuasion.

• Previous experience in democratizing data at scale for the enterprise is an advantage.

🏝️ Benefits

• Insurance coverage including medical, dental, vision, life, and disability.

• Flexible paid time off.

• Paid holidays.

• 401(k) plan with company matching.

• Remote work opportunities.