Wissen Infotech
Website:
wissen.com
Job details:
Job Description-
We are seeking a highly skilled Data Engineer to join our global data engineering team responsible for building and supporting enterprise-scale data platforms, data pipelines, and analytics solutions. The team develops and manages data messaging platforms and data repositories that store transactional, reference, and aggregated risk data for real-time and batch processing across operational data stores, archives, and data marts.
This role is primarily an Individual Contributor (IC)position with partial ownership of project delivery, stakeholder coordination, and technical leadership responsibilities. The ideal candidate will be hands-on in developing scalable data solutions while collaborating with globally distributed teams, business stakeholders, and support partners to ensure successful project execution.
Key Responsibilities
Data Engineering & Development
Design, develop, and maintain scalable and high-performance data pipelines using PySpark and Databricks.
Build and optimize ETL/ELT processes for processing large-scale structured and unstructured datasets.
Develop efficient data transformation frameworks and ingestion pipelines from multiple source systems.
Write high-quality, optimized SQL queries, stored procedures, and data processing logic.
Ensure data quality, reliability, scalability, and performance across data platforms.
Automate data processing and operational tasks through Python-based frameworks and scripting.
Participate in database design, data modeling, data integration, and optimization initiatives.
Technical Leadership & Project Ownership
Own and drive assigned workstreams from design through implementation and production deployment.
Collaborate with business users, product owners, architects, and cross-functional teams to translate business requirements into technical solutions.
Provide technical guidance to team members and contribute to solution design discussions.
Assist in project planning, effort estimation, prioritization, risk identification, and status tracking.
Ensure adherence to coding standards, best practices, and development lifecycle processes.
Support production issues, root cause analysis, and continuous improvement initiatives.
Innovation & AI Enablement
Leverage AI-powered development tools and modern engineering practices to improve development efficiency.
Explore and implement AI-driven solutions for business and operational challenges where applicable.
Must-Have Technical Skills
Core Skills (Mandatory)
Strong hands-on experience in PySpark development and distributed data processing.
Extensive experience working with Databricks for data engineering and analytics workloads.
Strong expertise in Python programming.
Advanced SQL skills with experience in query optimization and performance tuning.
Experience building and maintaining enterprise-scale ETL/ELT data pipelines.
Strong understanding of Data Lake, Lakehouse, and modern data engineering architectures.
Experience with relational databases and data modeling concepts.
Knowledge of Agile/Scrum development methodologies.
Excellent problem-solving and analytical skills.
Strong stakeholder management and communication abilities.
Good-to-Have Skills
Experience with Snowflake.
Knowledge of Spark optimization and performance tuning.
Experience with Kafka or event-driven data architectures.
Exposure to cloud platforms such as Azure, AWS, or GCP.
Experience with DevOps/CI-CD pipelines.
Knowledge of AI-powered development and productivity tools.
Familiarity with investment banking, capital markets, or financial services data domains.
Preferred Experience
8+ years of overall software/data engineering experience.
Hands-on experience with PySpark and Databricks.
Experience leading modules, workstreams, or small projects while remaining hands-on technically.
Proven ability to work effectively with globally distributed teams and stakeholders.
Experience mentoring junior engineers and contributing to technical decision-making.
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