Sr. Snowflake developer - NJ, NY (Onsite)

Smart Caliber Technology
New York, NY, United States
25 days ago
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Role details

Contract type
Temporary to permanent
Employment type
Full-time (> 32 hours)
Experience level
Expert
Compensation
$135,200.0 - $145,600.0
Working hours
Regular working hours

Tech stack

Java (Programming Language) Third Normal Form Agile Methodology Artificial Intelligence Airflow Amazon Web Services Amazon S3 Microsoft Azure Cloud Storage Software Documentation Databases Data Validation
+24 more
Data Deduplication Information Engineering Extract Transform Load (ETL) Data Profiling Data Stores Software Design Documents Java Database Connectivity Oracle (Applications) Systems Development Life Cycle Reference Data Standard Sql Requirements Management Software Engineering SQL Stored Procedures SQL Databases Systems Integration Workflow Management Systems Enterprise Data Management Snowflake Data Strategy Collibra Data Analytics Data Pipelines Sql Tuning

Job description

Drive performance analysis and optimization of SQL queries Oracle Snowflake troubleshoot complex data and systems issues and lead root cause analysis for data quality Partner with technology and business stakeholders to define requirements functional specifications and operational architecture for strategic global programs Provide input to data strategy and actively influence software development process improvements, Analyze optimize and benchmark SQL queries across Oracle and Snowflake diagnose and resolve highly complex performance and data quality issues through rigorous root cause analysis Collaborate with Universal Client Manager technology teams to define specifications design documents and functional use cases for system enhancements and integrations Elicit challenge and prioritize business requirements using standard processes and templates translate requirements into clear functional designs user stories and use case documentation Develop project scope objectives constraints and assumptions for large strategic multiyear initiatives ensure alignment to business outcomes and operational architecture Provide consultation to IT and business management on applying technology to business opportunities plan and guide implementation of crossfunctional applications and systems Participate in and provide guidance on technical design reviews test planning and user documentation ensure endtoend traceability from requirements through testing and release Manage scope changes and dependencies using formal requirements management principles including change control traceability and stakeholder signoffs Gather and analyze quantitative and qualitative data to develop recommendations addressing strategic objectives across multiple global business and technology areas Engage in industry forums to maintain current domain knowledge incorporate best practices into solution design and process improvements Apply experience with softwaresystems development processes to design and implement improved methodologies actively influence continuous improvement in SDLC and data practices May allocate and coordinate work within a team or project ensuring delivery quality and timeline adherence, Both the profile are AWS and Azure heavy and very less experience in relation Database, I have evaluated similar profile which is aligned towards pyspark based ingestion which is not the current requirement, Please find the below requirement * Oracle/Snowflake seasoned hands-on SQL

  • Tune and optimize SQL queries
  • Explain plan
  • Normalization and denormalization 2NF/3NF and dimensional models
  • Data quality , Data profiling
  • Understand Financial model Party and Party relationship

Best Regards, Chetna Truth Lies in Heart

Requirements

Must-have skills: SQL, Oracle, Snowflake, Collibra, Financial Domain Expertise. Good-to-have skills: Data Modeling, Banking Structures, AI, Data Analytics Exposure, Enterprise Data, SDLC Practices., Experience working with Collibra Proven expertise in SQL performance analysis and tuning across Oracle and Snowflake environments Hands on experience investigating and remediating data quality issues including root cause analysis and correctivepreventive actions Demonstrated ability to elicit and document business requirements and translate them into functional specifications use cases and technical designs Familiarity with operational architecture systems integration and crossfunctional application implementation Proficiency with requirements management practices change control traceability and participation in testing test plans UAT defect triage Strong stakeholder management and communication skills with the ability to consult and influence across business and technology teams Preferred Qualifications Experience working with Artificial Intelligence Experience working with Universal Client Manager or similar clientplatform technologies Exposure to largescale strategic multiyear programs spanning global business and technology areas Knowledge of modern SDLC practices agile methodologies and process improvement frameworks Participation in industry forums or professional communities related to data analytics or enterprise architecture Core Competencies Analytical problem solving and structured root cause analysis Requirements elicitation and prioritization Technical design literacy and testing rigor Data strategy awareness and business acumen Stakeholder engagement and consultative communication Process improvement and change management

  1. Snowflake Data Engineering - Hands-on experience designing and implementing data pipelines using Snowflake features including Streams, Tasks, Dynamic Tables, and Snowpipe for automated ingestion and incremental processing.
  2. SQL & Java Integration - Strong proficiency in complex SQL (window functions, CTEs, merge statements) and experience integrating Java-based ETL/ELT logic with Snowflake via JDBC or Snowflake connectors; familiarity with stored procedures and Snowpark is a plus.
  3. Data Curation & Modeling - Demonstrated experience building multi-layer lake architectures (raw curated consumption zones) with data quality checks, deduplication, and schema evolution handling for high-volume transactional datasets.
  4. Financial Domain Data - Prior exposure to financial data domains such as payment transactions, SWIFT messaging (MT/MX formats), customer inquiry records, or bank/client reference data; understanding of data sensitivity, masking, and compliance requirements.
  5. Datastore & Orchestration - Experience integrating Snowflake pipelines with external datastores (e.g., GCS, S3, Azure Blob, or relational DBs) and orchestration tools (e.g., Apache Airflow, dbt, or equivalent) for end-to-end pipeline scheduling

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