Ian Tynan’s Post

A Roadmap to Becoming a Data Engineer 🚀 In today's tech-driven world, data engineering is not just a role—it's a key driver of digital transformation. With top companies like Microsoft, Google, Amazon, and Adobe actively hiring for data engineering roles, now is the perfect time to gear up for this dynamic career. Whether you’re aiming to become a Big Data Engineer, Azure Data Engineer, or Data Consultant, these core skills will set you apart: 1️⃣ Relational Databases Master relational databases and T-SQL to handle data operations with tools like SQL Server, PostgreSQL, and MariaDB. 2️⃣ Programming Languages Strengthen your coding skills with Python, Scala, or Java to seamlessly integrate with AI and big data systems. 3️⃣ Big Data Tools Explore tools like Hadoop, PySpark, Hive, and Spark SQL to manage and process massive datasets effectively. 4️⃣ Cloud Platforms Dive into Azure, AWS, or GCP to work with cutting-edge cloud technologies like Azure Data Factory, Azure SQL, and Azure Data Lake Storage. 5️⃣ Data Warehousing Develop expertise in Synapse Analytics and Snowflake to translate raw data into actionable insights. 6️⃣ Real-Time Data Processing Equip yourself with tools like Apache Kafka and Azure Event Hubs to handle real-time data streams. 💡 Additional skills to boost your profile: * Airflow * DevOps * Tableau * MongoDB * Azure Cosmos DB Stay ahead by investing in continuous learning and adapting to emerging technologies. Remember, every skill you master brings you one step closer to your dream data engineering role! Let’s connect and exchange insights on this exciting journey 🚀 Follow SYED ARBAZ #DataEngineering #BigData #Cloud #CareerGrowth #ETL

🚀 Hey Data Engineers, Recruiters, and Data Managers! 🚀    I’ve just completed the Data Engineering with Databricks Learning Path, and I want to share my exciting journey with all of you. If you're hiring or building strong data teams, this post is for you!    This course was packed with hands-on learning and practical knowledge, covering essential concepts in data engineering. Here’s what I mastered along the way:    1️⃣ Getting Started with Databricks Data Science and Engineering Workspace    - I learned how to code efficiently and perform data engineering tasks using the Databricks platform.    2️⃣ Transforming Data with Spark (SQL/PySpark)    - I gained skills in using Spark SQL and PySpark to clean, transform, and analyze data from various sources.    3️⃣ Managing Data with Delta Lake    - I explored how to store, manage, and query massive datasets using Delta Lake for high-performance data operations.    4️⃣ Building Data Pipelines with Delta Live Tables (SQL/PySpark)    - I created pipelines to seamlessly load new data into the Lakehouse using Delta Live Tables.    5️⃣ Deploying Workloads with Databricks Workflows    - I automated data tasks and orchestrated pipelines with Databricks Workflow Jobs, ensuring everything runs smoothly.    6️⃣ Managing Data Access for Analytics with Unity Catalog    - I configured permissions to ensure proper access control for databases, keeping everything secure and organized.    Through this course, I sharpened my skills in ETL pipelines, Data Management, and Workflow Automation. I am now fully prepared to tackle real-world data challenges. If you're hiring, I’d love to bring these skills to your team!    💼 Let’s connect and explore opportunities to work together! I look forward to contributing to data projects and helping businesses thrive with data-driven insights.    Thank you for your time and interest!    #DataEngineering #Databricks #SparkSQL #ETL #DataLakehouse #Hiring

Urgent #Hiring || Databricks Feature Store/Data Engineer supporting || Machine Learning (ML) || New Jersey || 12+Years Please share resume at [email protected] Role: Databricks Feature Store/Data Engineer supporting Location: New Jersey  As a Data Engineer supporting Machine Learning (ML) initiatives, you will be responsible for using the Databricks Lakehouse Platform to complete advanced data engineering tasks. You will work closely with our data scientists and ML engineers to ensure that data is available, reliable, and optimized for their needs.   Key Responsibilities: 1. Cloud Data Architecture: Design and build robust data pipelines using Spark SQL and Python in both batch and incrementally processed paradigms orchestrated via Azure Data Factory. 2. Feature Engineering (Mandatory): Collaborate with data scientists to understand the features needed for ML models. Implement feature extraction and transformation logic in the data pipelines. 3. FeatureOps (Mandatory): Implement FeatureOps to manage the lifecycle of features including their discovery, validation, and serving for training and inference purposes. 4. Training Dataset Support: Work with data scientists to understand their requirements for training datasets. Ensure that these datasets are accurately prepared, cleaned, and made available in a timely manner. 5. Data Pipeline Automation: Automate the data pipelines using CI/CD approaches to ensure seamless deployment and updates. This includes automating tests, deployments, and monitoring of these pipelines. 6. Data Quality: Implement data quality frameworks and monitoring to ensure high data accuracy and reliability. Identify and resolve any data inconsistencies or anomalies. 7. Collaboration: Work closely with data scientists and ML engineers to understand their data needs. Provide them with the necessary data in the right format to facilitate their work. 8. Optimization: Continually optimize pipelines and databases for improved performance and efficiency. This includes implementing real-time processing where necessary. 9. Data Governance: Ensure compliance with data privacy regulations and best practices. Implement appropriate access controls and security measures. #c2c #benchsales #sales #hotlist #DataEngineer #Resume

If you don’t know these skills in 2024, you're not a data engineer 😱 🚨 The demand for data engineers is skyrocketing, but without these 10 must-have skills, you're missing out on massive opportunities. From Big Data to Cloud Computing, this is your roadmap to stay ahead in the game. Don’t wait—start upgrading your skills now! https://lnkd.in/gPT87dpv . . . . . #DataEngineer #BigData #Cloud #Tech #Skills #Engineering #Analytics #SQL #Hadoop #Spark #Python #ETL #AI #MachineLearning #Careers #Jobs #Trends #Opportunities #DataOps #Innovation #Growth #Development #Pipelines #Future #Professional #TechJobs #Career #Success #Upgrade #TechSkills #Strategy

🚀 Elevating Data Engineering Excellence! 🚀 As a seasoned Data Engineer with extensive experience in crafting scalable data solutions, I'm excited to connect with professionals and hiring managers in the industry! My journey in data engineering has equipped me with the skills to handle complex data pipelines, optimize ETL processes, and drive impactful data-driven decisions. 🔍 What I Bring to the Table: - Expertise in Data Pipelines: Designing and maintaining efficient ETL processes. - Proficiency in SQL & NoSQL: Extensive experience with SQL Server, Azure Data Factory, and more. - Advanced Analytics: Leveraging data to uncover insights and optimize operations. - Cloud Savvy: Skilled in Azure, AWS, and GCP for seamless data integration and management. 🌟 Let's Connect: I’m open to new opportunities where I can bring my passion for data engineering and problem-solving skills to make a difference. If your team is looking for someone who can transform data challenges into actionable insights, let's chat! 📩 Reach out if you're hiring or know someone who is! I'd love to explore how I can contribute to your organization's data success. #DataEngineering #DataScience #ETL #SQL #Azure #CloudData #DataSolutions #Hiring #JobSearch #DataPipelines

What qualities do you prioritize when hiring top Azure Data Engineers? With 9 years of hands-on experience in Azure Data Engineering and Business Intelligence, I’ve learned that technical skills are just one part of the equation. It’s crucial to evaluate problem-solving abilities, leadership, and how well candidates can align technical solutions with business needs. In my experience, finding engineers who not only excel in Azure cloud technologies but also demonstrate effective communication and collaboration is key to successful team dynamics and project outcomes. What do you focus on when assessing potential hires? #AzureDataEngineer #DataEngineering #AzureHiring #CloudSolutions #TechLeadership #AzureJobs #DataAnalytics #PowerBI #HiringTopTalent

DVA is not associated with this job post. Data Engineer - USA https://lnkd.in/gqiPu4U5 Our data team builds, augments, and maintains the infrastructure that empowers teams across Amplify and our customers to make sense of and tell stories with their data. We believe strongly in teaching our teammates to serve themselves, within a safe, reliable, and agile environment. You’ll be building data systems, but also the sharing-and-learning culture so that every team uses these tools to improve their own lives, and those of our students and teachers. Impress the toughest customers around – students – by: helping teams create fun, compelling apps by using millions of data points Make life better for passionate teachers by: helping teachers understand their students by building reusable data pipelines Make life better for passionate Data Science, Governance and Analyst teams by: Developing, Automating and Maintaining a scalable and secure data platform. Implementing and managing data storage solutions (e.g., data lakes, databases). Optimizing data processing and retrieval workflows. Collaborating with data scientists and analysts to facilitate data access and utilization. Ensuring data privacy and compliance with relevant regulations. Analyzing and Improving performance and squashing tricky bugs using tools like Snowflake, Airflow, dbt, SQL, Python, Looker, Terraform, and Datadog #jobseeker #jobsearch #jobs #job #jobseekers #hiring #jobsearching #recruitment #jobhunt #career #jobvacancy #jobinterview #employment #loker #nowhiring #jobboard #jobopportunity #recruiting #jobopening #resume #jobshiring #careers #work #interview #hiringnow #jobfair #recruiter #jobhunting #vacancy #jobseeking