Lazard
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Data Engineer
role at
Lazard
Americas | Corporate | New York
Lazard is one of the world’s preeminent financial advisory and asset management firms. Our people and culture make the difference. While global in presence and reach, our close, collaborative community of just over 3,000 professionals fosters continuous knowledge sharing, skill development and relationship building. Lazard’s entrepreneurial culture, flat structure and embrace of individual differences empower creative ideas, original concepts and unique perspectives to drive our business forward and help careers take flight.
The Lazard Data Analytics Group, composed of data scientists, AI engineers and software engineers, drives innovation by developing advanced AI and data science solutions that enhance decision-making across our financial advisory and asset management business lines. This team ensures Lazard stays at the forefront of a data‑driven world, delivering insights that support client engagements and strengthen key partnerships while keeping the firm competitive and efficient in an evolving financial landscape.
Responsibilities
Ingest and model data from APIs, files/SFTP, and relational sources; implement layered architectures (raw/clean/serving) using PySpark/SQL and dbt, Python.
Design and operate pipelines with Prefect (or Airflow), including scheduling, retries, parameterization, SLAs, and well‑documented runbooks.
Build on cloud data platforms, leveraging S3/ADLS/GCS for storage and a Spark platform (e.g., Databricks or equivalent) for compute; manage jobs, secrets, and access.
Publish governed data services and manage their lifecycle with Azure API Management (APIM) — authentication/authorization, policies, versioning, quotas, and monitoring.
Enforce data quality and governance through data contracts, validations/tests, lineage, observability, and proactive alerting.
Optimize performance and cost via partitioning, clustering, query tuning, job sizing, and workload management.
Uphold security and compliance (e.g., PII handling, encryption, masking) in line with firm standards.
Collaborate with stakeholders (analytics, AI engineering, and business teams) to translate requirements into reliable, production‑ready datasets.
Enable AI/LLM use cases by packaging datasets and metadata for downstream consumption, integrating via Model Context Protocol (MCP) where appropriate.
Continuously improve platform reliability and developer productivity by automating routine tasks, reducing technical debt, and maintaining clear documentation.
Qualifications
Bachelor’s or advanced degree in Computer Science, Data Engineering, or a related field.
4–15 years of professional data engineering experience.
Strong Python, SQL, and Spark (PySpark) skills, and/or Kafka.
Hands‑on experience building ETL/ELT with Prefect (or Airflow), dbt, Spark, and/or Kafka.
Experience onboarding datasets to cloud data platforms (storage, compute, security, governance).
Familiarity with Azure/AWS/GCP data services (e.g., S3/ADLS/GCS; Redshift/BigQuery; Glue/ADF).
Git‑based workflows CI/CD and containerization with Docker (Kubernetes a plus).
Bonus
Snowflake (Snowpipe, Tasks, Streams) as a complementary warehouse.
Databricks (Delta formats, workflows, cataloguing) or equivalent Spark platforms.
Advanced APIM practices (custom policies, OAuth2/JWT, mTLS, private endpoints) and Azure AD integration.
Integrating datasets into MCP tools/providers for LLM/agent applications; familiarity with frameworks such as LangChain or LlamaIndex.
Data observability/quality tools (e.g., Great Expectations, Monte Carlo, Datafold) and strong lineage practices.
Exposure to financial datasets and controls (PII handling, encryption, masking).
Benefits We strive to enhance the total health and well‑being of our employees through comprehensive, competitive benefits. Our goal is to offer a highly individualized employee experience that enables you to balance your commitments to career, family and community. Lazard cares about your unique talents and passions and will continue to invest in developing your career.
Compensation Base salary approximately $140,000 – $180,000 USD, with additional incentive compensation and comprehensive benefits.
Apply Does this sound like you? Apply! We’ll get in touch and let you know the next steps.
Representation at Lazard Lazard is an intellectual capital business committed to delivering the best advice and solutions to clients. We focus on attracting, developing and retaining the best talent. A workforce comprised of people who represent a wide array of backgrounds, experiences and perspectives creates a rich variety of thought that empowers us to challenge conventional wisdom, solve problems creatively and make better decisions. We are committed to sustaining an environment where every colleague is supported in their professional pursuits, can maximize their individual potential and contribute to our collective success.
#J-18808-Ljbffr
Data Engineer
role at
Lazard
Americas | Corporate | New York
Lazard is one of the world’s preeminent financial advisory and asset management firms. Our people and culture make the difference. While global in presence and reach, our close, collaborative community of just over 3,000 professionals fosters continuous knowledge sharing, skill development and relationship building. Lazard’s entrepreneurial culture, flat structure and embrace of individual differences empower creative ideas, original concepts and unique perspectives to drive our business forward and help careers take flight.
The Lazard Data Analytics Group, composed of data scientists, AI engineers and software engineers, drives innovation by developing advanced AI and data science solutions that enhance decision-making across our financial advisory and asset management business lines. This team ensures Lazard stays at the forefront of a data‑driven world, delivering insights that support client engagements and strengthen key partnerships while keeping the firm competitive and efficient in an evolving financial landscape.
Responsibilities
Ingest and model data from APIs, files/SFTP, and relational sources; implement layered architectures (raw/clean/serving) using PySpark/SQL and dbt, Python.
Design and operate pipelines with Prefect (or Airflow), including scheduling, retries, parameterization, SLAs, and well‑documented runbooks.
Build on cloud data platforms, leveraging S3/ADLS/GCS for storage and a Spark platform (e.g., Databricks or equivalent) for compute; manage jobs, secrets, and access.
Publish governed data services and manage their lifecycle with Azure API Management (APIM) — authentication/authorization, policies, versioning, quotas, and monitoring.
Enforce data quality and governance through data contracts, validations/tests, lineage, observability, and proactive alerting.
Optimize performance and cost via partitioning, clustering, query tuning, job sizing, and workload management.
Uphold security and compliance (e.g., PII handling, encryption, masking) in line with firm standards.
Collaborate with stakeholders (analytics, AI engineering, and business teams) to translate requirements into reliable, production‑ready datasets.
Enable AI/LLM use cases by packaging datasets and metadata for downstream consumption, integrating via Model Context Protocol (MCP) where appropriate.
Continuously improve platform reliability and developer productivity by automating routine tasks, reducing technical debt, and maintaining clear documentation.
Qualifications
Bachelor’s or advanced degree in Computer Science, Data Engineering, or a related field.
4–15 years of professional data engineering experience.
Strong Python, SQL, and Spark (PySpark) skills, and/or Kafka.
Hands‑on experience building ETL/ELT with Prefect (or Airflow), dbt, Spark, and/or Kafka.
Experience onboarding datasets to cloud data platforms (storage, compute, security, governance).
Familiarity with Azure/AWS/GCP data services (e.g., S3/ADLS/GCS; Redshift/BigQuery; Glue/ADF).
Git‑based workflows CI/CD and containerization with Docker (Kubernetes a plus).
Bonus
Snowflake (Snowpipe, Tasks, Streams) as a complementary warehouse.
Databricks (Delta formats, workflows, cataloguing) or equivalent Spark platforms.
Advanced APIM practices (custom policies, OAuth2/JWT, mTLS, private endpoints) and Azure AD integration.
Integrating datasets into MCP tools/providers for LLM/agent applications; familiarity with frameworks such as LangChain or LlamaIndex.
Data observability/quality tools (e.g., Great Expectations, Monte Carlo, Datafold) and strong lineage practices.
Exposure to financial datasets and controls (PII handling, encryption, masking).
Benefits We strive to enhance the total health and well‑being of our employees through comprehensive, competitive benefits. Our goal is to offer a highly individualized employee experience that enables you to balance your commitments to career, family and community. Lazard cares about your unique talents and passions and will continue to invest in developing your career.
Compensation Base salary approximately $140,000 – $180,000 USD, with additional incentive compensation and comprehensive benefits.
Apply Does this sound like you? Apply! We’ll get in touch and let you know the next steps.
Representation at Lazard Lazard is an intellectual capital business committed to delivering the best advice and solutions to clients. We focus on attracting, developing and retaining the best talent. A workforce comprised of people who represent a wide array of backgrounds, experiences and perspectives creates a rich variety of thought that empowers us to challenge conventional wisdom, solve problems creatively and make better decisions. We are committed to sustaining an environment where every colleague is supported in their professional pursuits, can maximize their individual potential and contribute to our collective success.
#J-18808-Ljbffr