Senior Data Engineer

Join our team as a Senior Data Engineer, where you will design, build, implement, and maintain data processing pipelines for ETL from various data sources. You will lead the writing of complex SQL queries, develop technical tools leveraging AI and machine learning, and evaluate and recommend tools for data infrastructure. You will work with structured and unstructured data, collaborate with various stakeholders, and enforce high standards for data governance and compliance.

About MeridianLink

Partner with stakeholders across engineering, finance, sales, and compliance to translate business requirements into reliable data models and workflows

Responsibilities

• Design, build, implement, and maintain data processing pipelines for ETL of data from various sources.
• Lead the writing of complex SQL queries and develop technical tools leveraging AI, machine learning, and big-data techniques.
• Evaluate and recommend tools and technologies for data infrastructure and processing, collaborating with stakeholders to translate business requirements.
• Enforce high standards for data governance, quality, lineage, and compliance
• Architect and scale our modern data platform to support real-time and batch processing for financial forecasting, risk analytics, and customer insights
• Evaluate emerging technologies and lead POCs that shape the future of our data stack
• Champion a culture of security, automation, and continuous delivery in all data workflows
• Deep expertise in Python, SQL, and distributed processing frameworks like Apache Spark, Databricks, Snowflake, Redshift, BigQuery

Requirements

• Experience working with structured and semi-structured data (e.g., Delta, JSON, Parquet, Avro) at scale
• Proven experience with cloud-based data platforms (preferably AWS or Azure)
• Hands-on experience with data orchestration tools (e.g., Airflow, dbt) and data warehouses (e.g., Databricks, Snowflake, Redshift, BigQuery)
• The role will include work on problems of diverse scopes where analysis of information requires evaluation of identifiable factors. Work is expected to be done independently through independent judgment
• 6-8 years of experience in data engineering, with a strong focus on financial systems on SaaS platforms
• Strong understanding of data security, privacy, and compliance within a financial services context
• Ability to enhance relationships and networks with senior internal partners who are not familiar with the subject often requires persuasion
• Previous experience Democratizing data at scale for the enterprise a huge plus
• Bachelor's or master's degree in computer science, Engineering, or a related field
• Familiarity with modelling datasets in Salesforce, Netsuite and Anaplan to solve business use cases required
• Ability to assess unusual circumstances and use sophisticated analytical and problem-solving techniques to identify the cause

Preferred

• Working with people, processes facing Enterprise a plus, improvement of processes/reduction of costs in the enterprise processes leveraging data is preferable

Pay

USD 95,000 - 135,000