Data Engineer

Job Summary

We are looking for a skilled and experienced Data Engineer to join our growing data team. The ideal candidate will have strong expertise in Python, PySpark, Data Modeling, and Power BI, with hands-on experience in designing, developing, and optimizing scalable data solutions. The role requires working closely with business stakeholders, data architects, and analytics teams to build robust data pipelines and semantic models that enable data-driven decision-making.

Technical Skills

• Strong hands-on experience in Python and PySpark development.
• Expertise in building and optimizing Data Engineering solutions and ETL pipelines.
• Strong understanding of Data Modeling concepts (Star Schema, Snowflake Schema, Dimensional Modeling).
• Experience with Power BI Data Modeling and Semantic Layer development.
• Proficiency in DAX (Data Analysis Expressions).
• Experience designing and managing Semantic Models in Power BI.
• Strong SQL skills and experience working with large datasets.
• Knowledge of data warehousing concepts and best practices.

Preferred Skills

• Experience with cloud platforms such as Azure, AWS, or GCP.
• Exposure to modern data platforms like Databricks.
• Understanding of data governance and data quality frameworks.

We are hiring a Databricks Data Engineer to build scalable data pipelines on the lakehouse.

Responsibilities

• Build batch and streaming pipelines in Databricks with PySpark
• Model data in Delta Lake
• Optimise Spark jobs for cost and performance
• Set up data quality checks and monitoring

Requirements

• 2+ years of data engineering with Databricks
• Strong PySpark and Spark SQL skills
• Cloud experience on Azure, AWS or GCP

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:

1. Design, develop, and maintain ETL/ELT pipelines using PySpark, Databricks, and Snowflake.
2. Develop batch and real-time data processing solutions for structured and semi-structured data.
3. Build and optimize Databricks notebooks, workflows, and Delta Lake solutions.
4. Design and implement Snowflake databases, schemas, views, stored procedures, tasks, and streams.
5. Develop scalable data models, data marts, and data warehouse solutions.
6. Optimize PySpark jobs, Databricks workloads, and Snowflake queries for performance and cost efficiency.
7. Implement data quality, validation, governance, and security controls.
8. Collaborate with business stakeholders, architects, and cross-functional teams to deliver data solutions.
9. Manage source control and CI/CD deployments using Git and Azure DevOps.
10. Troubleshoot production issues, perform root cause analysis, and ensure pipeline reliability.
11. 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.

Senior Data Engineer – PySpark & Oracle

Experience: 7+ Years

Location: Bangalore

Notice Period: Immediate to 10 Days

Key Skills:

• Strong expertise in Data Modeling, Data Design & Modernization
• Primary skills: PySpark, Oracle SQL/PLSQL
• Secondary skills: Python, ETL & Data Pipelines
• Experience with Kafka and Hadoop
• Exposure to AWS / Azure / GCP
• Good knowledge of Git and JIRA

Roles & Responsibilities:

• Design, develop, and modernize scalable data models and data architecture.
• Develop and optimize data processing solutions using PySpark and Oracle SQL/PLSQL.
• Build and maintain robust ETL workflows and data pipelines.
• Work with Kafka, Hadoop, and cloud platforms for data processing and integration.
• Perform data transformation, optimization, and performance tuning.
• Collaborate with technical teams on data design, development, testing, and deployment.

Define and obtain source data required to deliver insights and use cases.

● Determine data mapping and join multiple data sets across various sources.

● Develop methods to highlight and report data inconsistencies for user review.

● Propose and assist with suitable data migration sets for stakeholders.

● Support teams in processing data migration sets and coordinating migration activities.

● Plan, track, and coordinate the data migration team and migration run-book.

● Collaborate with stakeholders to avoid negative customer and business impacts.

● Ensure robust communication and escalation mechanisms across project portfolios.

● Implement strategic solutions and avoid short-term workarounds.

● Maintain strong control and compliance standards in data handling.

Required Skills

● Minimum 7+ years of experience as a Data Analyst, preferably in financial services.

● Strong expertise in Pyspark, Python, and SQL.

● Experience with big data programs and data models in banking or financial markets.

● Ability to write SQL queries and navigate databases such as Hive, CMD, Putty, and Note++.

● Excellent analytical skills and commercial acumen.

● Strong verbal and written communication skills.

● Proven ability to manage multiple priorities and deliver within tight deadlines.

● Business analysis skills, including defining and understanding requirements.

● Familiarity with SDLC, Agile processes, and a bias towards TDD.

● Attention to detail and a proactive, problem-solving mindset.

Nice to Have

● Knowledge and experience in Data Quality & Governance.

● Working experience with Spark Scala or Java for Spark.

● Proven track record of managing small, delivery-focused data teams (for senior roles).

● Experience with market data vendors and domains such as Party/Client, Trade, Settlements, Payments, Instrument and Pricing, Market and/or Credit Risk.

Data Engineer Hiring Post

🚨 Hiring: Data Engineer | PySpark + Python + SQL

We are looking for experienced Data Engineers to join our team!

🔹 Experience: 5 to 9 Years

🔹 Locations: Bangalore / Hyderabad

🔹 Interview Process:

• 1st Round – Virtual

• 2nd Round – Face-to-Face (Karat Test)

🔑 Key Skills:

✅ PySpark

✅ SQL

✅ Python

✅ ETL

📩 Interested candidates can share their updated resume.

#Hiring #DataEngineer #PySpark #Python #SQL #ETL #BangaloreJobs #HyderabadJobs #TechHiring #ImmediateHiring

🚨 WE ARE HIRING – SENIOR DATA ENGINEER | BANGALORE 🚨

Looking for experienced Senior Data Engineers with strong expertise in PySpark, Oracle SQL/PLSQL, and Data Modeling!

🔹 Role: Senior Data Engineer

🔹 Experience: 7+ Years

🔹 Location: Bangalore

🔹 CTC: Up to 26 LPA

🔹 Notice Period: Immediate to 10 Days Preferred

💻 Mandatory Skills

✅ PySpark

✅ Oracle SQL / PL/SQL

✅ Data Modeling & Design / Modernization

✅ Python

✅ ETL

✅ Data Pipelines

⚙️ Good to Have / Ecosystem Skills

✅ Kafka

✅ Hadoop

✅ AWS / Azure / GCP

✅ Git

✅ JIRA

📌 Key Responsibilities

• Develop and maintain scalable data pipelines using PySpark

• Work extensively with Oracle SQL/PLSQL for data processing and transformation

• Design and implement data models and data architecture

• Work on data design and modernization initiatives

• Develop and optimize ETL processes and data pipelines

• Handle large volumes of data using PySpark and Python

• Work with technologies such as Kafka, Hadoop, and Cloud platforms

• Collaborate with cross-functional teams to deliver scalable data solutions

• Use Git and JIRA for version control and project tracking

📩 Interested candidates can share their updated CV along with:

Total Experience:

Relevant PySpark Experience:

Relevant Oracle SQL/PLSQL Experience:

Data Modeling Experience:

Current Location:

Notice Period:

Current CTC:

Expected CTC:

#Hiring #DataEngineer #SeniorDataEngineer #PySpark #Oracle #PLSQL #DataModeling #Python #ETL #DataPipelines #Kafka #Hadoop #AWS #Azure #GCP #BangaloreJobs #ITJobs #TechJobs #ImmediateJoiners

Description

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.

Job Description – Azure Data Engineer

Role: Azure Data Engineer

Experience: 9+ Years

Location: Bangalore / Hyderabad

Notice Period: Immediate to 15 Days

Interview Process: 1st Round – Virtual | 2nd Round – F2F

Mandatory Skills

• Python
• PySpark
• SQL
• Azure Data Engineering

Job Description

We are looking for an experienced Azure Data Engineer with 9+ years of experience and strong hands-on expertise in Python, PySpark, SQL, and Azure Data Engineering.

Key Responsibilities

• Develop and maintain scalable data engineering solutions using Azure.
• Build and optimize data processing pipelines using PySpark and Python.
• Write complex SQL queries for data extraction and transformation.
• Work with Azure data services and cloud-based data platforms.
• Perform data processing, transformation, and integration.
• Troubleshoot data pipeline and production issues.
• Collaborate with technical and business teams to deliver data solutions.

Preferred: Immediate to 15 Days joiners.

We are looking for a Big Data Engineer to build large-scale data processing systems.

Responsibilities

• Build batch and streaming pipelines with Spark and Kafka
• Manage data in the Hadoop ecosystem (HDFS, Hive)
• Write Spark jobs in Scala or PySpark
• Tune jobs for performance and cost

Requirements

• 2+ years of big data engineering
• Strong hands-on Spark experience
• Experience with Hadoop, Hive and Kafka