Data Specialist

Key Skills

Algorithms, Amazon RedShift, Apache Hadoop, Apache Hive, Apache Kafka, AWS, Azure, Bash scripting, Big Data Technology, Data Analytics, Data Lake, Data pipelines, Data science techniques, Data Warehousing, ETL/ELT technologies, Google Cloud Platform (GCP), Java Programming, JavaScript, Machine learning techniques, MySQL, Oracle, PowerShell Programming, Presto, Python Programming, REST API, Scala Programming, Snowflake, SoapUI, SPARK Programming, SQL, SQL Server

Job Description

Are you a forward-thinking Data Engineer? Join our expanding team of analytics experts. We're seeking a Lead Data Engineer to enhance and optimize our data and pipeline architecture, enrich data flow and collection for cross-functional teams. Our ideal candidate is an adept data pipeline builder and wrangler, adept at constructing data systems from the ground up. As a Data Engineer, you'll collaborate with software developers, database architects, data analysts, and data scientists on various data initiatives, ensuring consistent and optimal data delivery architecture across ongoing projects. If you're self-directed and thrive in catering to diverse teams, systems, and products, and if you're excited by the chance to revamp our reference data architecture for our next-gen products and data strategies, we want to hear from you. 

Responsibilities

• Designing and implementing data and application integrations, as well as data pipelines on both existing and new information systems. 
• Constructing secure data pipelines, with a focus on automation through CI/CD techniques. 
• Identifying and resolving data quality issues in collaboration with the data team. 
• Preparing data for business users, data analysts, and data scientists. 

• Communicating directly with clients and product owners. 
• Supporting system design. 
• Assisting with issue triage, diagnosis, and resolution. 
• Collaborating on code reviews and solutions with other developers. 
• Contributing to system development methodologies and staying informed about evolving technologies, techniques, architectures, and hardware relevant to data management and platforms. 

• Playing a pivotal role in the introduction of new technologies and tools. 
• Ensuring robust data security through encryption, access controls, and authentication mechanisms to maintain data integrity and confidentiality across its lifecycle. 

Required Technical Expertise: 

• Proficiency in mainstream databases (e.g., SQL Server, Oracle, MySQL, DB2). 
• Deep knowledge of large-scale analytic database technologies (e.g., Snowflake, Redshift, Azure Synapse). 
• Experience constructing effective data pipelines. 
• Understanding of diverse Data & Analytics hybrid architectures, including Data Lake, Data Warehouse, Data Mesh, Enterprise Data Hub, Data Fabric, and Delta Lake with real-time, batch, and micro-batch workloads 
• Extensive Python experience. 

• Expertise in API programming interfaces such as JDBC, ODBC, REST API, and SOAP API. 
• Logging, auditing, and tracing knowledge. 
• Proficiency in SQL. 
• Intermediate Shell scripting skills (Bash, PowerShell, etc.). 
• Data security and privacy expertise. 

• Automation of data pipelines. 
• Infrastructure-as-code implementation (e.g., Liquibase, Flyway). 
• Hands-on experience with various data types (structured, semi-structured, unstructured, JSON, AVRO, ORC, Parquet, Iceberg, Arrow). 
• Data Quality Assurance mastery. 
• Knowledge of Big Data technologies (e.g., Hadoop, Hive, Spark, Kafka) and data engineering. 

• Expertise in Data Warehousing and Cloud Platforms (e.g., Snowflake, Redshift, Azure Synapse). 
• Proficiency in source code control using Git. 
• Understanding of Data Science and Machine Learning tools and algorithms. 

Desirable Skills: 

• Experience with major cloud technologies (AWS, GCP, Azure). 
• Data Application Development proficiency. 
• Data Modeling expertise. 
• Experience in large-scale data migrations. 

• Extensive experience with Spark and Databricks. 
• Proficiency in Scala, Java, and JavaScript. 
• Familiarity with AWS EMR and Presto. 
• Expertise in ETL/ELT tools (e.g., Informatica, Talend, DBT). 
• Knowledge of Data Replication (e.g., HVR, Golden Gate, Fivetran). 

• Understanding of Data Virtualization (e.g., Denodo). 
• Hands-on experience with machine learning. 
• Familiarity with Data Governance practices. 

Consultative Skills: 

• Dedication to adding value to projects and teams. 
• Flexibility and customer-centric approach. 
• Embracing feedback and showing growth. 
• Enthusiastic about continuous learning and professional development. 

• Identifying and addressing project challenges with Nortal leadership. 
• Understanding the high-level business value of ongoing projects. 
• Participation in mid-level technical meetings with clients. 
• Strong written and verbal English communication. 
• Self-directed work style. 

• Mentorship potential and orientation for Junior Engineers. 
• Initiative-driven and results-focused. 
• Openness to new experiences and knowledge. 
• Exceptional communication skills. 

Qualifications

• 3-5 years of Data Engineering experience. 
• Expert in SQL 
• In-depth experience with at least one programming language (e.g., Java, Python, Bash, JavaScript). 

Nortal is An Equal Opportunity Employer And All Qualified Applicants Will Receive Consideration For Employment Without Regard To Race, Color, Religion, Sex, National Origin, Disability Status, Protected Veteran Status, Or Any Other Characteristic Protected By Law.