Data Integration Lead (Streaming & Warehousing) Retail Wealth experience

  • Posted 1 hour ago | Updated 1 hour ago

Overview

Remote
Depends on Experience
Full Time

Skills

Data Integration
Retail Wealth
AWS
Data Architecture
ETL
Databricks
data governance
APEX

Job Details

Role: Data Integration Lead (Streaming & Warehousing) Retail Wealth experience

Location: Atlanta, GA / Windsor, CT

Mode Of Hire: Full Time


This is REMOTE JOB

Role

The role is a hands-on Data Engineering Lead to build streaming and batch data pipelines powering our digital selfservice roadmap. Design robust ETL/ELT on AWS, Kafka, Databricks, Oracle, and guide the transition to Snowflake. The role blends architecture and delivery owning data quality, observability, and governance in the Retail Wealth domain.

  • Domain Expertise: Deep experience in retail wealth, broker dealers, warehouses, family offices, custodians, trade order management, and digital self-service platforms (e.g., robo advisors).
  • Technical Stack: AWS, Kafka, Databricks, Oracle, Snowflake (future), ETL processes.
  • Hands-On Leadership: Integration lead must design/develop APIs and coordinate with architects; data lead must be strong in ETL/data integration.

Responsibilities

  • Design and build streaming & batch pipelines for ingestion, curation, and consumption (realtime + microbatch).
  • Engineer scalable ELT/ETL on Databricks (PySpark/Spark SQL), integrating sources including APEX, custodians, broker dealers, and market/reference data.
  • Optimize workloads on AWS (S3, Glue, EMR/Databricks, Lakehouse patterns); manage Oracle sources; drive Snowflake migration strategy and execution.
  • Enforce data quality (DQ), lineage, metadata, and governance with bestpractice frameworks and tooling.
  • Partner with analytics, product, and integration teams to support dashboards, operational reporting, advanced analytics, and ODS.
  • Establish DevSecOps for data (versioned transformations, CI/CD, IaC patterns, secrets mgmt).
  • Define and track SLAs/SLOs, cost controls, and performance baselines.

Must-Have Qualifications

5+ years (7+ preferred) in data engineering with lead-level ownership delivering production pipelines.

Retail Wealth expertise: custodians, broker dealers, warehouses/family offices; order/trade and position/transaction data.

Hands-on with Kafka (topics, partitions, schema/registry), Databricks (PySpark/Spark SQL), AWS data stack, and Oracle sources.

Strong SQL/performance tuning; ELT/ETL design patterns; batch orchestration (e.g., Airflow/Databricks Jobs).

Practical Data Governance: lineage, DQ, PII controls, encryption, RBAC, and regulatory awareness (FINRA/SEC).

Experience planning/executing Snowflake migrations (data modeling, performance, cost/pricing levers).

Nice to Have

  • Familiarity with Apex Fintech data domains and vendor ecosystems (Orion, Envestnet, Pershing/Schwab).
  • Knowledge of DTCC/NSCC, Morningstar data, advisory/UMA/SMA billing & commissions.
  • Observability for data (Great Expectations/Deequ, Delta Live Tables), cost optimization, and dbt or equivalent.
  • Bachelor s in CS/Engineering/Math/IS (Master s a plus).

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