Big Data Engineer at Affine · Remote only · 3 - 8 years · Profitable · Remote only · Posted 11 Dec 2024
Scala
Amazon Web Services (AWS)Role Objective:
Big Data Engineer will be responsible for expanding and optimizing our data and database architecture, as well as optimizing data flow and collection for cross functional teams. The ideal candidate is an experienced data pipeline builder and data wrangler who enjoys optimizing data systems and building. The Data Engineer will support our software developers, database architects, data analysts and data scientists on data initiatives and will ensure optimal data delivery architecture is consistent throughout ongoing projects. They must be self-directed and comfortable supporting the data needs of multiple teams, systems, and products
Roles & Responsibilities:
- Sound knowledge in Spark architecture and distributed computing and Spark streaming.
- Proficient in Spark – including RDD and Data frames core functions, troubleshooting and performance tuning.
- Good understanding in object-oriented concepts and hands on experience on Scala with excellent programming logic and technique.
- Good in functional programming and OOPS concept on Scala
- Good experience in SQL – should be able to write complex queries.
- Managing the team of Associates and Senior Associates and ensuring the utilization is maintained across the project.
- Able to mentor new members for onboarding to the project.
- Understand the client requirement and able to design, develop from scratch and deliver.
- AWS cloud experience would be preferable.
- Design, build and operationalize large scale enterprise data solutions and applications using one or more of AWS data and analytics services - DynamoDB, RedShift, Kinesis, Lambda, S3, etc. (preferred)
- Hands on experience utilizing AWS Management Tools (CloudWatch, CloudTrail) to proactively monitor large and complex deployments (preferred)
- Experience in analyzing, re-architecting, and re-platforming on-premises data warehouses to data platforms on AWS (preferred)
- Leading the client calls to flag off any delays, blockers, escalations and collate all the requirements.
- Managing project timing, client expectations and meeting deadlines.
- Should have played project and team management roles.
- Facilitate meetings within the team on regular basis.
- Understand business requirement and analyze different approaches and plan deliverables and milestones for the project.
- Optimization, maintenance, and support of pipelines.
- Strong analytical and logical skills.
- Ability to comfortably tackling new challenges and learn
External Skills And Expertise
Must have Skills:
- Scala
- Spark
- SQL (Intermediate to advanced level)
- Spark Streaming
- AWS preferable/Any cloud
- Kafka /Kinesis/Any streaming services
- Object-Oriented Programming
- Hive, ETL/ELT design experience
- CICD experience (ETL pipeline deployment)
Good to Have Skills:
- AWS Certification
- Git/similar version control tool
- Knowledge in CI/CD, Microservices
Shubham Vishwakarma
Full Stack Developer - Averlon
About Affine
About
Affine is a pioneering consulting firm that specializes in AI-driven enterprise transformation. With a robust focus on Generative AI, we deliver cutting-edge solutions that redefine industry standards.
Our comprehensive capabilities span the entire analytical value chain, from data to insights and transformation. We provide Cloud Advisory and Assessment, Cloud Migration, Data Lake Design and Development, Big Data Powered Advanced Analytics, AI & Deep Learning Solutions, and Deployment Consulting with Architecture Design.
Company social profiles
Similar jobs (10)
PythonScalaDescription
We are looking for Senior Data Engineers to join our Data Platform team and build scalable, high-performance data platforms that power data processing, analytics, and downstream applications.
The ideal candidate will have strong experience in distributed data processing, ETL pipelines, and Big Data technologies, with hands-on expertise in Apache Spark and Python Scala.
You will be responsible for designing, developing, and optimizing large-scale data pipelines while collaborating closely with cross-functional engineering teams to build reliable, production-grade data solutions.
Key Responsibilities
- Design, develop, and maintain scalable ETL and data processing pipelines for large-scale datasets.
- Build and optimize distributed data applications using Apache Spark and Python Scala.
- Develop reliable, high-performance data pipelines for batch and streaming workloads.
- Design and manage data workflows using Apache Airflow.
- Build and operate data workloads on AWS, with strong usage of Amazon S3 for large-scale data storage.
- Work with large datasets to ensure data quality, consistency, reliability, and performance.
- Collaborate with engineering, product, analytics, and other platform teams to deliver robust data solutions.
- Optimize data workflows for scalability, reliability, performance, and cost efficiency.
- Troubleshoot production issues, identify bottlenecks, and continuously improve platform performance.
Requirements
Candidates who demonstrate:
- 5+ years of experience in Data Engineering, Big Data Engineering, or a similar role.
- Strong hands-on experience with Apache Spark and Scala.
- Experience designing, building, and maintaining large-scale ETL pipelines.
- Strong hands-on experience with AWS, particularly Amazon S3.
- Hands-on experience with Apache Airflow for workflow orchestration and scheduling.
- Strong SQL skills and a solid understanding of distributed data processing concepts.
- Experience working with batch and/or streaming data pipelines.
- Excellent debugging, problem-solving, and performance optimization skills.
- Strong communication and collaboration skills.
Good to Have
- Experience with Databricks and the broader Databricks data platform.
- Familiarity with streaming technologies such as Apache Kafka.
- Experience working on large-scale data platforms handling high-volume data workloads.
- Exposure to additional AWS data services and cloud-native data architectures.
KubernetesScalaDescription
We are looking for Senior Data Engineers to join our AdTech team and build scalable, high-performance data platforms that power advertising insights and analytics. The ideal candidate will have strong experience in distributed data processing, ETL pipelines, and Big Data technologies, with hands-on expertise in Spark and Scala.
You will work on designing, developing, and optimizing large-scale data pipelines while collaborating closely with cross-functional engineering teams to build reliable, production-grade data solutions.
Key Responsibilities
- Design, develop, and maintain scalable ETL pipelines for large-scale data processing.
- Build and optimize distributed data applications using Spark and Scala.
- Develop reliable, high-performance data pipelines for batch and streaming workloads.
- Work with large datasets to ensure data quality, consistency, and performance.
- Collaborate with engineering, product, and analytics teams to deliver robust data solutions.
- Optimize data workflows for scalability, reliability, and cost efficiency.
- Deploy and manage data workloads in cloud and containerized environments.
- Troubleshoot production issues and continuously improve platform performance.
Requirements
Candidates who demonstrate:
- 5+ years of experience in Data Engineering or Big Data Engineering.
- Strong hands-on experience with Apache Spark and Scala.
- Experience building and maintaining ETL pipelines.
- Familiarity with Google Cloud Storage (GCS).
- Experience with Kubernetes (K8s).
- Strong SQL skills and understanding of distributed data processing.
- Excellent debugging, problem-solving, and performance optimization skills.
- Strong communication and collaboration skills.
Good to Have
- Experience with AWS and cloud-native data services.
- Familiarity with streaming technologies such as Kafka.
- Experience working on large-scale data platforms or AdTech systems.
- Exposure to orchestration tools such as Airflow.
Benefits
- Best-in-class salary: We hire strong talent and compensate accordingly.
- Proximity Talks: Meet and learn from designers, engineers, product leaders, and AI practitioners.
- Continuous learning: Work with a world-class team and stay close to the latest in AI, engineering, and product development.
- High-impact work: Build AI-first systems and products used at scale by global clients.
About Us
Proximity is the trusted technology, design, and consulting partner for some of the biggest Sports, Media, and Entertainment companies in the world. We’re headquartered in San Francisco and have offices in Palo Alto, Dubai, Mumbai, and Bangalore.
Since 2019, Proximity has built high-impact, scalable products used by millions of users every day. Today, we are a global team of engineers, designers, product managers, and experts solving complex problems and building cutting-edge technology at scale.
PythonScalaWe are hiring experienced Data Engineers for a permanent opportunity in Bangalore.
Job Description
Role: Data Engineer
Location: Bangalore
Experience: 6+ Years
Key Responsibilities:
- Design, develop, and maintain scalable data processing pipelines using Amazon EMR.
- Develop data engineering solutions using Python and Scala.
- Process and transform large volumes of structured and unstructured data.
- Build and optimize distributed data processing workflows for performance and scalability.
- Work with big data technologies and cloud-based data processing environments.
- Perform data integration, validation, transformation, and quality checks.
- Troubleshoot data pipeline issues and optimize processing performance.
- Collaborate with data architects, analysts, and development teams to deliver reliable data solutions.
Required Skills:
- Strong hands-on experience with Amazon EMR.
- Proficiency in Python and Scala.
- Experience in big data processing and data pipeline development.
- Good understanding of distributed computing and data transformation techniques.
- Experience in performance tuning and troubleshooting data processing jobs.
- Strong analytical, problem-solving, and communication skills.
Python1st virtual , 2nd round F2F
Python pyspark, SQL, data engineer
5+yrs
9+yrs
Bangalore/Hyderabad
immediate to 15days.
Pythonrole: data engineer
Python pyspark, SQL, data engineer
5+yrs
Bangalore/Hyderabad
immediate to 15days.
Responsibilities and JD
Job Description: We are looking for a Senior Developer with strong expertise in PySpark, Databricks, and Snowflake to build scalable data engineering solutions and enterprise data platforms.
Key Responsibilities:
- Design, develop, and maintain ETL/ELT pipelines using PySpark, Databricks, and Snowflake.
- Develop batch and real-time data processing solutions for structured and semi-structured data.
- Build and optimize Databricks notebooks, workflows, and Delta Lake solutions.
- Design and implement Snowflake databases, schemas, views, stored procedures, tasks, and streams.
- Develop scalable data models, data marts, and data warehouse solutions.
- Optimize PySpark jobs, Databricks workloads, and Snowflake queries for performance and cost efficiency.
- Implement data quality, validation, governance, and security controls.
- Collaborate with business stakeholders, architects, and cross-functional teams to deliver data solutions.
- Manage source control and CI/CD deployments using Git and Azure DevOps.
- Troubleshoot production issues, perform root cause analysis, and ensure pipeline reliability.
- Mentor junior team members and participate in code reviews and technical design discussions.
Required Skills: PySpark, Databricks, Snowflake, Python, SQL.
Experience: 5+ years of Data Engineering experience with strong hands-on expertise in PySpark, Databricks, and Snowflake.
JavaPythonWe are hiring for a Data Engineer & Java scala for a full-time opportunity in Bangalore.
Experience: 4–10 Years
Must-Have Skills:
Java / Scala / Python, Data Engineering, Databricks / Snowflake, and Cloud (AWS / Azure / GCP).
We are looking for strong software engineers with hands-on experience in data platform development, scalable backend programming, data integration, and cloud technologies.
Experience in Banking, Capital Markets, Market Risk, or Regulatory Reporting will be an added advantage.
Python1st virtual , 2nd round F2F -
Python pyspark, SQL, data engineer
5+yrs
Bang/hyderabad
immediate to 15days.
PythonAmazon Web Services (AWS)Data Architect – Databricks & AWS
- Strong experience in Data Architecture, Data Engineering, Databricks, Apache Spark/PySpark, Python, and Advanced SQL.
- Design and implement scalable ETL/ELT pipelines, data platforms, and Lakehouse architectures using Medallion Architecture.
- Experience with Databricks, Databricks Workflows, Unity Catalog OR Databricks Jobs
- Strong knowledge of Delta Lake, Databricks Workflows, Delta Live Tables (DLT), and dimensional data modeling.
- Hands-on experience with AWS services such as S3, Glue, IAM, Lambda, and CloudWatch.
- Experience with Apache Airflow, Data Warehouse concepts, Git/CI-CD, performance optimization, and data quality.
- Good to have exposure to Kafka/Structured Streaming, Unity Catalog, and modern data governance.
PythonAbout the Role
We are looking for a Senior Data Engineer with strong hands-on expertise in Databricks, Python, PySpark, and SQL to build scalable, high-performance data engineering solutions. You’ll architect and develop large scale, high-performance data pipelines capable of handling massive real-time and batch data volumes across multiple business systems. Databricks is the core enterprise data and processing platform for this role. You will also use Apache Airflow for workflow orchestration and dbt for ELT transformations, and will contribute to designing reliable, secure, and governed data platforms that enable analytics, reporting, and AI-driven use cases.
Key Responsibilities
- Design and implement large-scale data pipelines using Python/PySpark, Databricks, and Microsoft Fabric.
- Develop and optimize data processing workloads in Databricks using PySpark and Spark SQL, with a strong focus on scalability, reliability, performance, and maintainability.
- Develop and maintain dbt models including layered architecture, incremental models, snapshots, macros, testing, and documentation.
- Design, develop, and maintain Apache Airflow DAGs for orchestrating reliable, scalable, and observable data pipelines.
- Design and implement data quality, observability, and governance frameworks, including automated testing, monitoring, lineage, access control, and data privacy standards.
- Partner with analytics, product, and business stakeholders to turn requirements into trustworthy datasets, and raise the engineering bar through design discussions, code reviews, and mentoring junior engineers.
Required Skills
- Strong expertise in Python for developing scalable, modular, and production-ready data engineering applications.
- Strong expertise in PySpark, including DataFrame API, Spark SQL, Structured Streaming, partitioning strategies, joins, caching, handling data skew, and Spark performance optimization.
- Strong hands-on experience with Databricks for data ingestion, transformation, processing, and optimization, including Delta Lake, Unity Catalog, Databricks Workflows, notebooks, jobs, and Databricks-native data engineering capabilities.
- Strong experience in Databricks/Spark performance tuning, including query and job optimization, partitioning, file sizing, caching, join optimization, handling data skew, and efficient use of compute resources.
- Hands-on experience with Delta Lake, including transactional data processing, schema management, incremental data processing, and reliable batch and streaming data pipelines.
- Hands-on experience in developing dbt projects using layered architecture, incremental models, snapshots, macros/Jinja, testing, documentation, and deployment best practices.
- Expertise in advanced SQL and data modelling — dimensional modeling, slowly changing dimensions, schema evolution, and query optimization.
- Hands-on experience in developing and managing Apache Airflow DAGs, scheduling workflows, dependency management, retries, backfills, and operational monitoring.
- Hands-on experience with at least one major cloud platform (AWS, Azure or GCP).
- Strong problem-solving skills and the ability to work independently with business and analytics stakeholders.
Nice to Have
- Hands-on exposure to Microsoft Fabric for data integration and analytics.
- Experience using AI coding assistants (e.g. Claude Code, GitHub Copilot) as part of a development workflow.
- Familiarity with modern DevOps practices, including CI/CD pipelines, Infrastructure as Code (IaC), and containerization (Docker/Kubernetes).
- Domain expertise in financial services.
Follow CutshortShubham Vishwakarma
Full Stack Developer - Averlon